Identification of hub genes to regulate breast cancer metastasis to brain by bioinformatics analyses

Rotenoids from the Roots of Vicia faba L. (Fabaceae): Structural Characterization, Cytotoxic Effects, and Molecular Docking

The chemical study of the ethanolic extract from the roots of Vicia faba led to the isolation of two isoflavonoids, alfalone and 8-O-methylretusine, as well as a mixture of rotenoids, including clitoriacetal and clitoriacetal B, the latter of which is reported for the first time. These compounds were characterized through nuclear magnetic resonance and vibrational circular dichroism spectroscopies, and density functional theory calculations. The rotenoid mixture exhibited cytotoxic activity against HCT-116, MCF-7, and 501Mel cell lines, while showing no significant toxicity to NIH/3T3 cells. The predictive analysis identified several shared therapeutic targets across colorectal cancer, breast cancer, and melanoma. Key sites, including hypoxia-inducible factor 1-alpha (HIF1A), estrogen receptor, heat shock protein HSP 90-beta, and heat shock protein HSP 90-alpha, were highlighted for their critical roles in tumor progression and therapeutic resistance. Notably, clitoriacetal demonstrated an affinity for HIF1A, suggesting its involvement in the observed antitumor effects, likely through modulation of the HIF1A pathway. These findings underscore the potential of V. faba root-derived compounds as promising candidates for targeted cancer therapies.

Prediction of new candidate proteins and analysis of sub-modules and protein hubs associated with seed development in rice (Oryza sativa) using an ensemble network-based systems biology approach

BACKGROUND

Rice is a critical global food source, but it faces challenges due to nutritional deficiencies and the pressures of a growing population. Understanding the molecular mechanisms and protein functions in rice seed development is essential to improve yield and grain quality. However, there is still a significant knowledge gap regarding the key proteins and their interactions that govern rice seed development. Protein-protein interaction (PPI) analysis is a powerful tool for studying developmental processes like seed development, though its potential in rice research is yet to be fully realized. With the aim of unraveling the protein interaction landscape associated with rice seed development, this systems biology study conducted a PPI network-based analysis. Using a list of known seed development proteins from the Gene Ontology (GO) knowledgebase and literature, novel candidate proteins for seed development were predicted using an ensemble of network-based algorithms, including Majority Voting, Hishigaki Algorithm, Functional Flow, and Random Walk with Restart, which were selected based on their popularity and usability. The predictions were validated using enrichment analysis and cross-checked with independent transcriptomic analysis results. The rice seed development sub-network was further analyzed for community and hub detection.

RESULTS

The study predicted 196 new proteins linked to rice seed development and identified 14 sub-modules within the network, each representing different developmental pathways, such as endosperm development and seed growth regulation. Of these, 17 proteins were identified as intra-modular hubs and 6 as inter-modular hubs. Notably, the protein SDH1 emerged as a dual hub, acting as both an intra-modular and inter-modular hub, highlighting its importance in seed development PPI network stability.

CONCLUSIONS

These findings, including the identified hub proteins and sub-modules, provide a better understanding of the PPI interaction landscape governing seed development in rice. This information is useful for achieving a systems biology understanding of seed development. This study implements an ensemble of algorithms for the analysis and showcases how systems biology techniques can be applied in developmental biology.

Focal adhesion in the tumour metastasis: from molecular mechanisms to therapeutic targets

The tumour microenvironment is the "hotbed" of tumour cells, providing abundant extracellular support for growth and metastasis. However, the tumour microenvironment is not static and is constantly remodelled by a variety of cellular components, including tumour cells, through mechanical, biological and chemical means to promote metastasis. Focal adhesion plays an important role in cell-extracellular matrix adhesion. An in-depth exploration of the role of focal adhesion in tumour metastasis, especially their contribution at the biomechanical level, is an important direction of current research. In this review, we first summarize the assembly of focal adhesions and explore their kinetics in tumour cells. Then, we describe in detail the role of focal adhesion in various stages of tumour metastasis, especially its key functions in cell migration, invasion, and matrix remodelling. Finally, we describe the anti-tumour strategies targeting focal adhesion and the current progress in the development of some inhibitors against focal adhesion proteins. In this paper, we summarize for the first time that focal adhesion play a positive feedback role in pro-tumour metastatic matrix remodelling by summarizing the five processes of focal adhesion assembly in a multidimensional way. It is beneficial for researchers to have a deeper understanding of the role of focal adhesion in the biological behaviour of tumour metastasis and the potential of focal adhesion as a therapeutic target, providing new ideas for the prevention and treatment of metastases.

SKA1/2/3 is a prognostic and predictive biomarker in esophageal adenocarcinoma and squamous cell carcinoma

BACKGROUND

Esophageal carcinoma (ESCA) ranks among the most prevalent malignant tumors globally. Despite significant advancements in treatment options and improved patient outcomes, the 5-year survival rate remains unsatisfactory. The spindle and kinetochore associated complex subunit 1/2/3 (SKA1/2/3) attached to the kinetochore (KT) in the metaphase of mitosis are implicated in the occurrence and development of various tumors. However, the expression patterns, diagnostic significance and prognostic implications of SKA1/2/3 in ESCA have not been comprehensively determined.

METHODS

TCGA, UALCAN, Kaplan-Meier Plotter, and TIMER databases were leveraged to dissect the expression patterns, prognostic implications and diagnostic value of SKA1/2/3 in ESCA patients, as well as to investigate the potential regulatory mechanism of SKA1/2/3 in the onset and progression of ESCA.

RESULTS

In ESCA, SKA1/2/3 exhibited substantial expression, with higher levels relating significantly with clinicopathological features and patient prognosis. Enrichment analysis of genes co-expressed with SKA1/2/3 highlighted their involvement in the cell cycle, DNA replication and p53 signaling pathway. Protein-protein interaction (PPI) analysis identified ten hub genes that were not only markedly upregulated but also portended a poor prognosis in ESCA. Additionally, immune infiltration assays uncovered a significant link between SKA1/2/3 expression and the immune cell infiltration within ESCA. Silencing of SKA1/2/3 significantly suppresses cell proliferation and migration, while concurrently promoting apoptosis in ESCA cells.

CONCLUSIONS

SKA1/2/3 may serve as promising biomarkers for the prognosis and diagnosis of ESCA, which holds promise as a novel therapeutic target for the disease.

Identification of Hub of the Hub-Genes From Different Individual Studies for Early Diagnosis, Prognosis, and Therapies of Breast Cancer

Breast cancer (BC) is a complex disease, which causes of high mortality rate in women. Early diagnosis and therapeutic improvements may reduce the mortality rate. There were more than 74 individual studies that have suggested BC-causing hub-genes (HubGs) in the literature. However, we observed that their HubG sets are not so consistent with each other. It may be happened due to the regional and environmental variations with the sample units. Therefore, it was required to explore hub of the HubG (hHubG) sets that might be more representative for early diagnosis and therapies of BC in different country regions and their environments. In this study, we selected top-ranked 10 HubGs (CCNB1, CDK1, TOP2A, CCNA2, ESR1, EGFR, JUN, ACTB, TP53, and CCND1) as the hHubG set by the protein-protein interaction network analysis based on all of 74 individual HubG sets. The hHubG set enrichment analysis detected some crucial biological processes, molecular functions, and pathways that are significantly associated with BC progressions. The expression analysis of hHubGs by box plots in different stages of BC progression and BC prediction models indicated that the proposed hHubGs can be considered as the early diagnostic and prognostic biomarkers. Finally, we suggested hHubGs-guided top-ranked 10 candidate drug molecules (SORAFENIB, AMG-900, CHEMBL1765740, ENTRECTINIB, MK-6592, YM201636, masitinib, GSK2126458, TG-02, and PAZOPANIB) by molecular docking analysis for the treatment against BC. We investigated the stability of top-ranked 3 drug-target complexes (SORAFENIB vs ESR1, AMG-900 vs TOP2A, and CHEMBL1765740 vs EGFR) by computing their binding free energies based on 100-ns molecular dynamic (MD) simulation based Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) approach and found their stable performance. The literature review also supported our findings much more for BC compared with the results of individual studies. Therefore, the findings of this study may be useful resources for early diagnosis, prognosis, and therapies of BC.

KDM5 family as therapeutic targets in breast cancer: Pathogenesis and therapeutic opportunities and challenges

Breast cancer (BC) is the most frequent malignant cancer diagnosis and is a primary factor for cancer deaths in women. The clinical subtypes of BC include estrogen receptor (ER) positive, progesterone receptor (PR) positive, human epidermal growth factor receptor 2 (HER2) positive, and triple-negative BC (TNBC). Based on the stages and subtypes of BC, various treatment methods are available with variations in the rates of progression-free disease and overall survival of patients. However, the treatment of BC still faces challenges, particularly in terms of drug resistance and recurrence. The study of epigenetics has provided new ideas for treating BC. Targeting aberrant epigenetic factors with inhibitors represents a promising anticancer strategy. The KDM5 family includes four members, KDM5A, KDM5B, KDM5C, and KDMD, all of which are Jumonji C domain-containing histone H3K4me2/3 demethylases. KDM5 proteins have been extensively studied in BC, where they are involved in suppressing or promoting BC depending on their specific upstream and downstream pathways. Several KDM5 inhibitors have shown potent BC inhibitory activity in vitro and in vivo, but challenges still exist in developing KDM5 inhibitors. In this review, we introduce the subtypes of BC and their current therapeutic options, summarize KDM5 family context-specific functions in the pathobiology of BC, and discuss the outlook and pitfalls of KDM5 inhibitors in this disease.

SKA3 Expression as a Prognostic Factor for Patients with Pancreatic Adenocarcinoma

The spindle and kinetochore-associated complex subunit 3 (SKA3) is a protein essential for proper chromosome segregation during mitosis and thus responsible for maintaining genome stability. Although its involvement in the pathogenesis of various cancer types has been reported, the potential clinicopathological significance of SKA3 in pancreatic ductal adenocarcinoma (PDAC) has not been fully elucidated. Therefore, this study aimed to assess clinicopathological associations and prognostic value of SKA3 in PDAC. For this purpose, in-house immunohistochemical analysis on tissue macroarrays (TMAs), as well as a bioinformatic examination using publicly available RNA-Seq dataset, were performed. It was demonstrated that SKA3 expression at both mRNA and protein levels was significantly elevated in PDAC compared to control tissues. Upregulated mRNA expression constituted an independent unfavorable prognostic factor for the overall survival of PDAC patients, whereas altered SKA3 protein levels were associated with significantly better clinical outcomes. The last observation was particularly clear in the early-stage tumors. These findings render SKA3 a promising prognostic biomarker for patients with pancreatic ductal adenocarcinoma. However, further studies are needed to confirm this conclusion.

SKA3 targeted therapies in cancer precision surgery: bridging bench discoveries to clinical applications - review article

Spindle and kinetochore-associated complex subunit 3 (SKA3) is a microtubule-binding subcomplex of the outer kinetochore, which plays a vital role in proper chromosomal segregation and cell division. Recently, SKA3 have been demonstrated its oncogenic role of tumorigenesis and development in cancers. In this review, the authors comprehensively deciphered SKA3 in human cancer from various aspects, including bibliometrics, pan-cancer analysis, and narrative summary. The authors also provided the top 10 predicted drugs targeting SKA3. The authors proposed that SKA3 was a potential target and brought new therapeutic opportunities for cancer patients.

Knockdown of GNL3L Alleviates the Progression of COPD Through Inhibiting the ATM/p53 Pathway

Background

Chronic obstructive pulmonary disease (COPD) is a persistent chronic bronchitis disease, and its potential biomarkers have not been fully expounded. This study aims to explore the role of Guanine nucleotide binding protein like-3-like (GNL3L) in COPD induced by cigarette smoking (CS) in vivo.

Methods

Two microarray datasets of COPD were selected to screen differentially expressed genes (DEGs). A protein-protein interaction network was constructed to find hub genes. The COPD model was conducted using CS/LPS-induced mouse and cigarette smoke extract induced human bronchial epithelial cells. The pathological changes of lung tissue in mice were observed by hematoxylin-eosin staining and mean linear intercept. Cell viability was measured by CCK8 assay. Oxidative stress-related indicators, inflammatory factors, and ATM/p53 related-proteins were assessed using ELISA and Western blot.

Results

In this study, there were 110 common DEGs identified from the two datasets (GSE5058 and GSE38974). The key gene GNL3L was the optimal indicator to distinguish between samples with COPD and healthy controls. Through the in vivo and in vitro experiments, GNL3L knockdown significantly improved the pathological features of CS/LPS-induced COPD mice, promoted cell viability, inhibited inflammation (IL-1β, IL-8, and TNF-α), oxidative stress (MDA, SOD, and CAT), and ATM/p53 related-proteins (ATM, p53, and p21).

Conclusion

GNL3L is a novel biomarker of COPD, and knockdown of GNL3L participates in the progression of COPD by inhibiting ATM/p53 pathway.

Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer

Background and Objectives: Breast cancer (BC) is one of the major causes of cancer-related death in women globally. Proper identification of BC-causing hub genes (HubGs) for prognosis, diagnosis, and therapies at an earlier stage may reduce such death rates. However, most of the previous studies detected HubGs through non-robust statistical approaches that are sensitive to outlying observations. Therefore, the main objectives of this study were to explore BC-causing potential HubGs from robustness viewpoints, highlighting their early prognostic, diagnostic, and therapeutic performance. Materials and Methods: Integrated robust statistics and bioinformatics methods and databases were used to obtain the required results. Results: We robustly identified 46 common differentially expressed genes (cDEGs) between BC and control samples from three microarrays (GSE26910, GSE42568, and GSE65194) and one scRNA-seq (GSE235168) dataset. Then, we identified eight cDEGs (COL11A1, COL10A1, CD36, ACACB, CD24, PLK1, UBE2C, and PDK4) as the BC-causing HubGs by the protein-protein interaction (PPI) network analysis of cDEGs. The performance of BC and survival probability prediction models with the expressions of HubGs from two independent datasets (GSE45827 and GSE54002) and the TCGA (The Cancer Genome Atlas) database showed that our proposed HubGs might be considered as diagnostic and prognostic biomarkers, where two genes, COL11A1 and CD24, exhibit better performance. The expression analysis of HubGs by Box plots with the TCGA database in different stages of BC progression indicated their early diagnosis and prognosis ability. The HubGs set enrichment analysis with GO (Gene ontology) terms and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways disclosed some BC-causing biological processes, molecular functions, and pathways. Finally, we suggested the top-ranked six drug molecules (Suramin, Rifaximin, Telmisartan, Tukysa Tucatinib, Lynparza Olaparib, and TG.02) for the treatment of BC by molecular docking analysis with the proposed HubGs-mediated receptors. Molecular docking analysis results also showed that these drug molecules may inhibit cancer-related post-translational modification (PTM) sites (Succinylation, phosphorylation, and ubiquitination) of hub proteins. Conclusions: This study's findings might be valuable resources for diagnosis, prognosis, and therapies at an earlier stage of BC.

Evaluation of breast tumor morphologies from African American and Caucasian patients

The primary aim of this research was to investigate potential differences of breast tumor morphologies across African American and Caucasian racial groups by utilizing machine learning (ML) and artificial intelligence (AI) methods. While breast cancer disparities can partially be attributed to social determinants of health, tumor biology also contributes to survival outcomes. The rate of breast tumor growth is largely dependent on the extracellular matrix (ECM). Current research suggests the cellular components of the ECM may vary among racial and ethnic populations, and this may contribute to the incidence of cancer in African Americans. We utilized a supervised AI method to evaluate morphological differences between African American and Caucasian breast cancer tumors. Images used for analysis were downloaded from the Cancer Genome Atlas (TCGA) biorepository stored in the NIH Genomic Data Commons (GDC) data portal. We designed an ML classifier using the AlexNet model provided in PyTorch's torchvision package. The model was pre-trained and adapted via transfer learning resulting in a classification accuracy of 92.1% when using our breast cancer tumor image database split into 80% of training set and 20% of testing set. We interpreted the results of the AlexNet and ResNet50 models using LIME and saliency mapping as the explainers. Based on the images from our bi-racial testing set, this study confirmed significant variations of tumor and ECM regions in the different racial groups evaluated. Based on these findings, further analysis and characterization may provide new insight into disparities associated with the incidence of breast cancer.

Clinical Prognostic Implications of Wnt Hub Genes Expression in Medulloblastoma

Medulloblastoma is the most common type of pediatric malignant primary brain tumor, and about one-third of patients die due to disease recurrence and most survivors suffer from long-term side effects. MB is clinically, genetically, and epigenetically heterogeneous and subdivided into at least four molecular subgroups: WNT, SHH, Group 3, and Group 4. We evaluated common differentially expressed genes between a Brazilian RNA-seq GSE181293 dataset and microarray GSE85217 dataset cohort of pediatric MB samples using bioinformatics methodology in order to identify hub genes of the molecular subgroups based on PPI network construction, survival and functional analysis. The main finding was the identification of five hub genes from the WNT subgroup that are tumor suppressors, and whose lower expression is related to a worse prognosis for MB patients. Furthermore, the common genes correlated with the five tumor suppressors participate in important pathways and processes for tumor initiation and progression, as well as development and differentiation, and some of them control cell stemness and pluripotency. These genes have not yet been studied within the context of MB, representing new important elements for investigation in the search for therapeutic targets, prognostic markers or for understanding of MB biology.

The Investigation of the Molecular Mechanism of Morinda officinalis How in the Treatment of Heart Failure

Heart failure (HF) is a cardiovascular disease with an extremely high mortality rate. However, Morinda officinalis How (MO) has not been studied for cardiovascular purposes at this time, the aim of this study was to find new mechanism for the MO of treatment of HF through a bioinformatics and experimental validation. The present study also aimed to establish a link between the basic and clinical applications of this medicinal herb. MO compounds and targets were obtained by traditional Chinese medicine systems pharmacology (TCMSP) and Pubchem. Subsequently, HF targets were acquired from DisGeNET and the interactions of all the targets and other human proteins were obtained via String so as to establish a component-target interaction network by Cytoscape 3.7.2. All the targets of clusters were inserted into Database for Annotation, Visualization and Integrated Discovery (DAVID) to perform GO (gene ontology) enrichment analysis. Molecular docking was adopted to predict the targets of MO relevant to the treatment of HF and to further explore the associated pharmacological mechanisms. Subsequently, a series of in vitro experiments, including histopathological staining, immunohistochemical and immunofluorescence analyses were conducted for further verification. Moreover, western blot analysis and in vivo experiments were performed. The results indicated that MO alleviated apoptosis, regulated cholesterol metabolism and transport function, and reduced inflammation, which resulted in the successful treatment of HF. Beta-sitosterol, Asperuloside tetraacetate and americanin A were the key bioactive components of MO. ALB, AKT1, INS, STAT3, IL-6, TNF, CCND1, CTNNB1, CAT, and TP53 were the core potential targets, which were significantly associated with multiple pathways, namely the FoxO signaling pathway, the AMPK signaling pathway, and the HIF-1 signaling pathway. In vivo experiments validated that MO may protect against heart failure or treat this disease by increasing the levels of autophagy via the FoxO3 signaling pathway in rats. The present study suggested that a combination of network pharmacology prediction with experimental validation may offer a useful tool to characterize the molecular mechanism of action of the traditional Chinese medicine (TCM) MO in the treatment of HF.

Nano-Enabled Strategies for the Treatment of Lung Cancer: Potential Bottlenecks and Future Perspectives

On a global scale, lung cancer is acknowledged to be the major driver of cancer death attributable to treatment challenges and poor prognosis. Classical cancer treatment regimens, such as chemotherapy or radiotherapy, can be used to treat lung cancer, but the appended adverse effects limit them. Because of the numerous side effects associated with these treatment modalities, it is crucial to strive to develop novel and better strategies for managing lung cancer. Attributes such as enhanced bioavailability, better in vivo stability, intestinal absorption pattern, solubility, prolonged and targeted distribution, and the superior therapeutic effectiveness of numerous anticancer drugs have all been boosted with the emergence of nano-based therapeutic systems. Lipid-based polymeric and inorganic nano-formulations are now being explored for the targeted delivery of chemotherapeutics for lung cancer treatment. Nano-based approaches are pioneering the route for primary and metastatic lung cancer diagnosis and treatment. The implementation and development of innovative nanocarriers for drug administration, particularly for developing cancer therapies, is an intriguing and challenging task in the scientific domain. The current article provides an overview of the delivery methods, such as passive and active targeting for chemotherapeutics to treat lung cancer. Combinatorial drug therapy and techniques to overcome drug resistance in lung cancer cells, as potential ways to increase treatment effectiveness, are also discussed. In addition, the clinical studies of the potential therapies at different stages and the associated challenges are also presented. A summary of patent literature has also been included to keep readers aware of the new and innovative nanotechnology-based ways to treat lung cancer.

Integrative transcriptome analysis of triple negative breast cancer profiles for identification of druggable targets

As triple negative breast cancer (TNBC) lacks a specific target, exploration of abnormally expressed genes during the progression of TNBC is important for a better understanding of tumorigenesis and to find a specific target. We intended to figure out genes associated with TNBC, which can provide unique insights into gene dysregulation in TNBC while also pointing to new possible therapeutic targets for TNBC. A meta-analysis of multiple TNBC mRNA profiles was performed to identify consistently differentially expressed genes (CDGs). The pathways involved in modulating these genes were analyzed by MsigDB, and the interaction map was constructed. These CDGs were evaluated for their expression in cell lines, and drugs that could modulate the expression of CDGs were obtained using the connectivity map. CDGs were docked with doxorubicin and anethole, which is a phytocompound. The expression of selected CDGs was analyzed in MDA-MB-231 cells after treatment with doxorubicin and anethole. We found 45 CDGs, out of which 36 were upregulated and 9 were downregulated. MDA-MB-231 cell line was found to have high expression of CDGs, and drug that could modulate the expression of CDGs was doxorubicin. Docking results revealed that anethole and doxorubicin had good interaction with the CDGs especially with the genes AURKA, CDC6, DEPDC1, KIF23, KPNA2, MELK, CTNNB1, FLI1 and E2F1. Gene expression studies of the selected CDGs showed that the synergistic effect of anethole and doxorubicin effectively downregulated the expression. The CDGs identified from multiple cohorts have clinical significance and may be effectively exploited in the targeted therapy for TNBC.Communicated by Ramaswamy H. Sarma.

Anterior Gradient 2 is a Significant Prognostic Biomarker in Bone Metastasis of Breast Cancer

Background: The study aimed to detect DEGs associated with BRCA bone metastasis, filter prognosis biomarkers, and explore possible pathways.

Methods: GSE175692 dataset was used to detect DEGs between BRCA bone metastatic cases and non-bone metastatic cases, followed by the construction of a PPI network among DEGs. The main module among the PPI network was then determined and pathway analysis on genes within the module was performed. Through performing Cox regression, Kaplan-Meier, nomogram, and ROC curve analyses using GSE175692 and GSE124647 datasets at the same time, the most significant prognostic biomarker was gradually filtered. Finally, important pathways associated with prognostic biomarkers were explored by GSEA analysis.

Results: The 74 DEGs were detected between bone metastasis and non-bone metastasis groups. A total of 15 nodes were included in the main module among the whole PPI network and they mainly correlated with the IL-17 signaling pathway. We then performed Cox analysis on 15 genes using two datasets and only enrolled the genes with p < 0.05 in Cox analysis into the further analyses. Kaplan-Meier analyses using two datasets showed that the common biomarker AGR2 expression was related to the survival time of BRCA metastatic cases. Further, the nomogram determined the greatest contribution of AGR2 on the survival probability and the ROC curve revealed its optimal prognostic performance. More importantly, high expression of AGR2 prolonged the survival time of BRCA bone metastatic patients. These results all suggested the importance of AGR2 in metastatic BRCA. Finally, we performed the GSEA analysis and found that AGR2 was negatively related to IL-17 and NF-kβ signaling pathways.

Conclusion: AGR2 was finally determined as the most important prognostic biomarker in BRCA bone metastasis, and it may play a vital role in cancer progression by regulating IL-17 and NF-kB signaling pathways.

MCluster-VAEs: An end-to-end variational deep learning-based clustering method for subtype discovery using multi-omics data

The discovery of cancer subtypes based on unsupervised clustering helps in providing a precise diagnosis, guide treatment, and improve patients' prognoses. Instead of single-omics data, multi-omics data can improve the clustering performance because it obtains a comprehensive landscape for understanding biological systems and mechanisms. However, heterogeneous data from multiple sources raises high complexity and different kinds of noise, which are detrimental to the extraction of clustering information. We propose an end-to-end deep learning based method, called Multi-omics Clustering Variational Autoencoders (MCluster-VAEs), that can extract cluster-friendly representations on multi-omics data. First, a unified network architecture with an attention mechanism was developed for accurately modeling multi-omics data. Then, using a novel objective function built from the Variational Bayes technique, the model was trained to effectively obtain the posterior estimation of the clustering assignments. Compared with 12 other state-of-the-art multi-omics clustering methods, MCluster-VAEs achieved an outstanding performance on benchmark datasets from the TCGA database. On the Pan Cancer dataset, MCluster-VAEs achieved an adjusted Rand index of approximately 0.78 for cancer category recognition, an increase of more than 18% compared with other methods. Furthermore, a survival analysis and clinical parameter enrichment tests conducted on 10 cancer datasets demonstrated that MCluster-VAEs provides comparable and even better results than many common integrative approaches. These results demonstrate that MCluster-VAEs are a powerful new tool for dissecting complex multi-omics relationships and providing new insights for cancer subtype discovery.

Comprehensive Analysis Identifies COL1A1, COL3A1, and POSTN as Key Genes Associated with Brain Metastasis in Patients with Breast Cancer

Objective

Brain metastasis (BM) is associated with a high mortality in patients with breast cancer (BC). Nevertheless, the molecular mechanisms of BM in BM remain uncertain. The study aims to identify the key genes in BC in relation to BM and to assess their prognostic value.

Methods

Two microarray datasets GSE125989 and GSE100534 were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) between primary BC and BM samples. The function enrichment analysis and protein-protein interaction (PPI) network were performed. We mapped hub genes into the Kaplan–Meier database for their correlations with BC survival.

Results

Venn diagram analysis showed an overlapped upregulated DEG and 18 overlapped downregulated ones between primary BC and BM samples. We constructed the PPI network, and top 5 hub genes were sorted out according to the node degree, including type I collagen α₁ chain (COL1A1), lumican (LUM), type III collagen α₁ chain (COL3A1), type V collagen α₂ chain (COL5A2), and periosteal protein (POSTN). The Kaplan–Meier database analysis found that COL1A1, COL3A1, and POSTN were significantly correlated with overall survival of BC patients.

Conclusion

The study suggests that COL1A1, COL3A1, and POSTN may be key genes associated with BM in patients with BC.

Prominin 1 Significantly Correlated with Bone Metastasis of Breast Cancer and Influenced the Patient’s Prognosis

Background

This study is aimed at identifying the important biomarkers associated with bone metastasis (BM) in breast cancer (BRCA).

Methods

The GSE175692 dataset was used to detect significant differential expressed genes (DEGs) between BRCA samples with or without BM, and DEG-related pathways were then explored. Further, we constructed the protein-protein interaction (PPI) network on GEGs and filtered 5 vital nodes. We then performed the Cox regression, Kaplan-Meier analysis, nomogram, and ROC curve to filter the most significant prognosis genes. The GSE14020 and GSE124647 datasets were used to verify the expression and prognostic value of hub genes, respectively. Finally, the gene set enrichment analysis (GSEA) was performed to reveal the potential mechanism.

Results

Totally, 74 DEGs were detected, which mainly correlated with infectious disease, signaling molecules, and interaction. The 5 important DEGs were then filtered, and the Cox regression further showed that 2 genes, including prominin 1 (PROM1) and C-C motif chemokine ligand 2 (CCL2), were related to the prognosis of BRCA metastasis patients. Especially, PROM1 presented a better prognostic performance on the survival probability of patients than CCL2. Verification analysis further confirmed the abnormal expression and significant prognostic influence of PROM1. Finally, GSEA revealed that PROM1 was negatively related to IGF1 and mTOR pathways in BRCA metastasis.

Conclusion

PROM1 was an important biomarker associated with BRCA bone metastasis and affected the prognosis of metastatic BRCA patients. It may play a vital role in metastatic BRCA by negatively regulating IGF1 and mTOR pathways.

C1R, CCL2, and TNFRSF1A Genes in Coronavirus Disease-COVID-19 Pathway Serve as Novel Molecular Biomarkers of GBM Prognosis and Immune Infiltration

Glioblastoma multiforme (GBM) is a prevalent intracranial brain tumor associated with a high rate of recurrence and treatment difficulty. The prediction of novel molecular biomarkers through bioinformatics analysis may provide new clues into early detection and eventual treatment of GBM. Here, we used data from the GTEx and TCGA databases to identify 1923 differentially expressed genes (DEGs). GO and KEGG analyses indicated that DEGs were significantly enriched in immune response and coronavirus disease-COVID-19 pathways. Survival analyses revealed a significant correlation between high expression of C1R, CCL2, and TNFRSF1A in the coronavirus disease-COVID-19 pathway and the poor survival in GBM patients. Cell experiments indicated that the mRNA expression levels of C1R, CCL2, and TNFRSF1A in GBM cells were very high. Immune infiltration analysis revealed a significant difference in the proportion of immune cells in tumor and normal tissue, and the expression levels of C1R, CCL2, and TNFRSF1A were associated with immune cell infiltration of GBM. Additionally, the protein-protein interaction networks of C1R, CCL2, and TNFRSF1A involved a total of 65 nodes and 615 edges. These results suggest that C1R, CCL2, and TNFRSF1A may be used as molecular biomarkers of prognosis and immune infiltration in GBM patients in the future.

Protein-protein interaction networks as miners of biological discovery

Protein-protein interactions (PPIs) form the basis of a myriad of biological pathways and mechanism, such as the formation of protein-complexes or the components of signaling cascades. Here, we reviewed experimental methods for identifying PPI pairs, including yeast two-hybrid, mass spectrometry, co-localization, and co-immunoprecipitation. Furthermore, a range of computational methods leveraging biochemical properties, evolution history, protein structures and more have enabled identification of additional PPIs. Given the wealth of known PPIs, we reviewed important network methods to construct and analyze networks of PPIs. These methods aid biological discovery through identifying hub genes and dynamic changes in the network, and have been thoroughly applied in various fields of biological research. Lastly, we discussed the challenges and future direction of research utilizing the power of PPI networks. This article is protected by copyright. All rights reserved.

Nanomedicine Strategies for Management of Drug Resistance in Lung Cancer

Lung cancer (LC) is one of the leading causes of cancer occurrence and mortality worldwide. Treatment of patients with advanced and metastatic LC presents a significant challenge, as malignant cells use different mechanisms to resist chemotherapy. Drug resistance (DR) is a complex process that occurs due to a variety of genetic and acquired factors. Identifying the mechanisms underlying DR in LC patients and possible therapeutic alternatives for more efficient therapy is a central goal of LC research. Advances in nanotechnology resulted in the development of targeted and multifunctional nanoscale drug constructs. The possible modulation of the components of nanomedicine, their surface functionalization, and the encapsulation of various active therapeutics provide promising tools to bypass crucial biological barriers. These attributes enhance the delivery of multiple therapeutic agents directly to the tumor microenvironment (TME), resulting in reversal of LC resistance to anticancer treatment. This review provides a broad framework for understanding the different molecular mechanisms of DR in lung cancer, presents novel nanomedicine therapeutics aimed at improving the efficacy of treatment of various forms of resistant LC; outlines current challenges in using nanotechnology for reversing DR; and discusses the future directions for the clinical application of nanomedicine in the management of LC resistance.

Comparative analysis of protein-protein interaction networks in metastatic breast cancer

Metastatic lesions leading causes of the majority of deaths in patients with the breast cancer. The present study aimed to provide a comprehensive analysis of the differentially expressed genes (DEGs) in the brain (MDA-MB-231 BrM2) and lung (MDA-MB-231 LM2) metastatic cell lines obtained from breast cancer patients compared with those who have primary breast cancer. We identified 981 and 662 DEGs for brain and lung metastasis, respectively. Protein-protein interaction (PPI) analysis revealed seven shared (PLCB1, FPR1, FPR2, CX3CL1, GABBR2, GPR37, and CXCR4) hub genes between brain and lung metastasis in breast cancer. Moreover, GNG2 and CXCL8, C3, and PTPN6 in the brain and SAA1 and CCR5 in lung metastasis were found as unique hub genes. Besides, five co-regulation of clusters via seven important co-expression genes (COL1A2, LUM, SPARC, THBS2, IL1B, CXCL8, THY1) were identified in the brain PPI network. Clusters screening followed by biological process (BP) function and pathway enrichment analysis for both metastatic cell lines showed that complement receptor signalling, acetylcholine receptor signalling, and gastric acid secretion pathways were common between these metastases, whereas other pathways were site-specific. According to our findings, there are a set of genes and functional pathways that mark and mediate breast cancer metastasis to the brain and lungs, which may enable us understand the molecular basis of breast cancer development in a deeper levele to the brain and lungs, which may help us gain a more complete understanding of the molecular underpinnings of breast cancer development.

Overexpression of SKA3 correlates with poor prognosis in female early breast cancer

BACKGROUND

Spindle and kinetochore associated complex subunit 3 (SKA3) plays an important role in tumorigenesis and the progression of various tumors. But the relationship between SKA3 and early breast cancer remains unclear. The study aimed to explore the prognostic significance of SKA3 in breast cancer.

METHODS

In the study, SKA3 expression was initially assessed using the Oncomine database and The Cancer Genome Atlas database (TCGA). Then, we presented validation results for RT-qPCR (quantitative reverse transcription PCR) and ELISA (enzyme-linked immunosorbent assay). The relationship between clinical characteristics and SKA3 expression was assessed by Chi-square test and Fisher's exact test. Kaplan-Meier method and Cox regression analysis were conducted to evaluate the prognostic value of SKA3. Gene set enrichment analysis (GSEA) was performed to screen biological pathways using the TCGA dataset. Besides, single sample gene set enrichment analysis (ssGSEA) was utilized to identify immune infiltration cells about SKA3.

RESULTS

SKA3 mRNA was expressed at high levels in breast cancer tissues compared with normal tissues. Chi-square test and Fisher's exact test showed SKA3 expression was related to age, tumor (T) classification, node (N) classification, tumor-node-metastasis (TNM) stage, estrogen receptor (ER), progesterone receptor (PR), molecular subtype, and race. RT-qPCR results showed that SKA3 expression was overexpressed in ER, PR status, and molecular subtype in Chinese people. Kaplan-Meier curves implicated that high SKA3 expression was related to a poor prognosis in female early breast cancer patients. Cox regression models showed that high SKA3 expression could be used as an independent risk factor for female early breast cancer. Four signaling pathways were enriched in the high SKA3 expression group, including mTORC1 signaling pathway, MYC targets v1, mitotic spindle, estrogen response early. Besides, the SKA3 expression level was associate with infiltrating levels of activated CD4 T cells and eosinophils in breast cancer.

CONCLUSION

High SKA3 expression correlates with poor prognosis and immune infiltrates in breast cancer. SKA3 may become a biomarker for the prognosis of breast cancer.

Genetic association between major depressive disorder and type 2 diabetes mellitus: Shared pathways and protein networks

BACKGROUND

Major depressive disorder (MDD) and type 2 diabetes mellitus (T2DM) are common public health disorders that often co-occur. This study aims to determine whether gene expression profiles from individuals with MDD or T2DM overlap and if there are any functional interconnectivity between identified genes using protein-protein interaction (PPI).

METHODS

The DNA microarray datasets were extracted from the Gene Expression Omnibus. Gene expression dataset GSE98793 from a case-control study of MDD (64 healthy control subjects, 128 patients) and dataset GSE15653 from a case-control study of T2DM (nine controls, nine individuals with T2DM) were used for this secondary and post-hoc analysis. GO enrichment analyses and Reactome pathway enrichment analysis were performed for functional enrichment analyses with the shared genes. PPI networks, PPI clusters and hub genes were performed to detect the potential relationships among differentially expressed genes (DEG) -encoding proteins in both MDD and T2DM.

RESULTS

A total of 3640 DEGs were identified in the MDD group when compared to the control group, whereas 3700 DEGs were identified in the T2DM group when compared to the control groups, among which 244 DEGs were overlap genes. The identified DEGs were enriched for Interleukin-4 and Interleukin-13 signaling, neutrophil degranulation, as well as other select species of the innate immune system. The biological processes of neurofibrillary tangle assembly regulation, tau-protein kinase activity regulation, amyloid-beta clearance regulation, amyloid-beta formation regulation and neuron apoptotic processes were also identified. Molecular function analysis indicated that identified genes were mainly enriched for amyloid-beta binding. 925 out of 1006 protein-protein interactions and six sub-networks were identified reflecting the disparate biological domains of overlapping genes. Ten hub genes further highlight the putative importance of tau-protein kinase activity, inflammatory response and neuron apoptotic regulatory processes across MDD and T2DM.

CONCLUSIONS

Our results indicate that an overlapping genetic architecture subserves MDD and T2DM. Genes relevant to the innate immune system, tau protein formation, and cellular aging were identified. Results indicate that the common, often comorbid, conditions of MDD and T2DM have a pathoetiologic nexus.

Identification of the Potential Prognosis Biomarkers in Hepatocellular Carcinoma: An Analysis Based on WGCNA and PPI

Aim

This study was done to determine biomarkers for the prognostic prediction of hepatocellular carcinoma (HCC).

Materials and Methods

In the Gene Expression Omnibus, the gene expression profiles of HCC were downloaded. Biomarkers were identified by weighted gene co-expression network analysis and protein–protein interaction network analysis.

Results

There were 24 modules, which were characterized by the high correlation with HCC. Meanwhile, through enrichment analysis, differentially expressed genes were largely participated in the ubiquitination and autophagy processes. Moreover, PRC1, TOP2A and CKAP2L may be the hub genes involved in HCC tumorigenesis, and their biomarker roles were further demonstrated via Gene Expression Profiling Interactive Analysis (GEPIA) and Oncomine databases. In addition, the levels of PRC1, TOP2A and CKAP2L were obviously up-regulated in the sera of HCC patients.

Conclusion

PRC1, TOP2A and CKAP2L may serve as biomarkers for the prognostic prediction of HCC patients.

Identification of potential genes related to breast cancer brain metastasis in breast cancer patients

Brain metastases (BMs) usually develop in breast cancer (BC) patients. Thus, the molecular mechanisms of breast cancer brain metastasis (BCBM) are of great importance in designing therapeutic strategies to treat or prevent BCBM. The present study attempted to identify novel diagnostic and prognostic biomarkers of BCBM. Two datasets (GSE125989 and GSE100534) were obtained from the Gene Expression Omnibus (GEO) database to find differentially expressed genes (DEGs) in cases of BC with and without brain metastasis (BM). A total of 146 overlapping DEGs, including 103 up-regulated and 43 down-regulated genes, were identified. Functional enrichment analysis showed that these DEGs were mainly enriched for functions including extracellular matrix (ECM) organization and collagen catabolic fibril organization. Using protein-protein interaction (PPI) and principal component analysis (PCA) analysis, we identified ten key genes, including LAMA4, COL1A1, COL5A2, COL3A1, COL4A1, COL5A1, COL5A3, COL6A3, COL6A2, and COL6A1. Additionally, COL5A1, COL4A1, COL1A1, COL6A1, COL6A2, and COL6A3 were significantly associated with the overall survival of BC patients. Furthermore, COL6A3, COL5A1, and COL4A1 were potentially correlated with BCBM in human epidermal growth factor 2 (HER2) expression. Additionally, the miR-29 family might participate in the process of metastasis by modulating the cancer microenvironment. Based on datasets in the GEO database, several DEGs have been identified as playing potentially important roles in BCBM in BC patients.

SKA3 overexpression predicts poor outcomes in skin cutaneous melanoma patients

BACKGROUND

Spindle and Kinetochore Associated Complex Subunit 3 (SKA3) is a part of the SKA complex, which plays a key role in cell mitosis. Studies have shown that SKA3 was associated with cancer progression. However, its role in skin cutaneous melanoma (SKCM) remains unclear. Here, we investigated the expression level and prognostic value of SKA3 in SKCM.

METHODS

Based on public databases, univariate and multivariate Cox regression analyses were used to investigate the different expression of SKA3 between SKCM and normal tissues. Then, the relationship between SKA3 expression level and prognosis was assessed. PPI network and functional enrichment analysis were performed. ESTIMATE and CIBERSORT were expected to evaluate the SKA3 expression and immune status. CCK8, wound healing, transwell assays and tumor xenograft trial were performed to detect the SKA3 function in cell viability, migration and invasion of the cell lines.

RESULTS

The SKA3 was highly expressed in SKCM tissues. SKA3 overexpression was associated with poor survival and immune status. SKA3 knockdown inhibited cell viability, migration and invasion of SKCM cells.

CONCLUSION

SKA3 is involved in the progression of SKCM and may serve as a new prognostic biomarker and therapeutic target.

Key genes affecting the progression of nasopharyngeal carcinoma identified by RNA-sequencing and bioinformatic analysis

Background: The present work was conducted to screen the potential biomarkers affecting nasopharyngeal carcinoma (NPC) progression through RNA-sequencing (RNA-seq), bioinformatic analysis and functional experiments.

Materials and Methods: Six normal samples and five NPC clinical samples were collected for RNA-seq analysis. The expression levels in both groups were determined through student’s t-test. We identified genes of P < 0.01 as the differentially expressed genes (DEGs). In addition, gene set enrichment analysis (GSEA) was conducted. Afterwards, STRING V10 database was employed to extract protein interactions among the DEGs. Later, we established a protein-protein interaction (PPI) network, and used the Cytoscape software for network visualization. qRT-PCR was conducted to verify hub genes from clinical samples. Then, the function of CXCL10 in cell proliferation, apoptosis, invasion and migration was evaluated.

Results: A total of 2024 DEGs were identified, among which, 1449 were down-regulated and 575 were up-regulated. The PPI was constructed, and the hub genes including Insulin Like Growth Factor 1 (IGF1), C-X-C Motif Chemokine Ligand 10 (CXCL10), Interleukin 13 (IL13), Intercellular Adhesion Molecule 1 (ICAM1), G Protein Subunit Gamma Transducin 1 (GNGT1), Matrix Metallopeptidase 1 (MMP1), Neurexin 1 (NRXN1) and Matrix Metallopeptidase 3 (MMP3) were obtained. The expression levels of CXCL10, IGF1, MMP3, MMP1, ICAM1, and IL-13 were significantly up-regulated in tumor tissues. High expression levels of CXCL10, MMP3 and ICAM1 predicted poor prognosis of NPC patients. CXCL10 silencing suppressed NPC cell proliferation and migration.

Conclusions: CXCL10 may serve as a potential key gene affecting NPC genesis and progression.

Comprehensive analysis of differentially expressed long noncoding RNAs, miRNAs and mRNAs in breast cancer brain metastasis

Aim: To delineate the transcriptomic landscape and potential molecular mechanisms of breast cancer brain metastasis (BCBM). Materials & methods: Whole-transcriptome sequencing was performed to identify long noncoding RNA (lncRNA), miRNA and mRNA expression profiles associated with BCBM. Results: A total of 739 differentially expressed lncRNAs, 115 differentially expressed miRNAs and 5749 differentially expressed mRNAs were identified in 231-BR cells compared with MDA-MB-231 cells. Real-time quantitative PCR results revealed the expression levels of candidate molecules were consistent with their correspondence RNA-seq data. Protein-protein interaction analysis identified some hub genes associated with BCBM, such as PTBP1, NUP98 and HYOU1. LncRNA-miRNA-mRNA network highlighted a potential mechanism of BCBM in which lncRNA FIRRE and RP11-169F17.1 sponging hsa-miR-501-5p to regulate the expression of MMS19, PTBP1 and NUP98. Conclusion: This study provides a framework for better understanding molecular mechanisms of BCBM.

miR-4319 Suppresses the Growth of Esophageal Squamous Cell Carcinoma Via Targeting NLRC5

BACKGROUND

The functions of microRNAs (miRNAs) in cancer progression have been recognized in recent years. However, the role of miR-4319 in esophageal squamous cell carcinoma (ESCC) remains unclear.

OBJECTIVE

We aimed to investigate the biological roles of miR-4319 in ESCC progression and the associated mechanisms.

METHODS

Real-time PCR was performed to examine the levels of miR-4319 in ESCC cell lines. The effects of miR-4319 and NOD-like receptor (NLR) family, caspase activation and recruitment domain (CARD) domain containing 5 (NLRC5) on cell proliferation and cell cycle progression were evaluated using MTT assay, colony formation and flow cytometry assays. Bioinformatics techniques and luciferase reporter assay were applied to validate NLRC5 as a miR-4319 target.

RESULTS

The miR-4319 expression was lower in ESCC cells than in the normal cell line. The expression of miR-4319 repressed cell growth and induced cell cycle arrest. NLRC5 was validated as a direct downstream target of miR-4319. Overexpression of NLRC5 potentiated the effects of miR-4319 on cell growth and cell cycle distribution.

CONCLUSION

Our results demonstrated that miR-4319 might function as a tumor suppressor by targeting NLRC5 in ESCC.

KIF4A knockdown suppresses ovarian cancer cell proliferation and induces apoptosis by downregulating BUB1 expression

Ovarian cancer is one of the most common lethal gynecological malignancies worldwide. Abnormal kinesin family member 4A (KIF4A) expression has been implicated in ovarian cancer progression; however, the potential mechanism underlying KIF4A in ovarian cancer is not completely understood. The present study aimed to clarify the molecular basis of KIF4A in ovarian cancer. KIF4A and budding uninhibited by benzimidazoles 1 (BUB1) expression levels were detected via reverse transcription-quantitative PCR and western blotting. Cell Counting Kit-8, colony formation, wound healing, TUNEL and flow cytometry assays were performed to assess cell proliferation, migration, apoptosis and cell cycle distribution, respectively. Ki67 expression levels were detected by conducting immunofluorescence assays. The expression levels of migration- and apoptosis-related proteins were measured via western blotting. A co-immunoprecipitation assay was conducted to determine the association between KIF4A and BUB1. The results demonstrated that KIF4A was expressed at significantly higher levels in ovarian cancer cell lines compared with IOSE-80 cells. Compared with the short hairpin RNA-negative control group, KIF4A knockdown significantly inhibited cell viability, colony formation and migration, and markedly induced cell apoptosis. The results indicated that KIF4A could bind to BUB1 and regulate BUB1 expression. BUB1 overexpression weakened KIF4A knockdown-mediated effects on cell viability, colony formation, migration and apoptosis. Overall, the present study demonstrated that KIF4A knockdown suppressed ovarian cancer progression by regulating BUB1, and suggested the potential value of KIF4A and BUB1 as therapeutic targets for ovarian cancer.

Identification of Hub Genes to Regulate Breast Cancer Spinal Metastases by Bioinformatics Analyses

Breast cancer (BC) had been one of the deadliest types of cancers in women worldwide. More than 65% of advanced-stage BC patients were identified to have bone metastasis. However, the molecular mechanisms involved in the BC spinal metastases remained largely unclear. This study screened dysregulated genes in the progression of BC spinal metastases by analyzing GSE22358. Moreover, we constructed PPI networks to identify key regulators in this progression. Bioinformatics analysis showed that these key regulators were involved in regulating the metabolic process, cell proliferation, Toll-like receptor and RIG-I-like receptor signaling, and mRNA surveillance. Furthermore, our analysis revealed that key regulators, including C1QB, CEP55, HIST1H2BO, IFI6, KIAA0101, PBK, SPAG5, SPP1, DCN, FZD7, KRT5, and TGFBR3, were correlated to the OS time in BC patients. In addition, we analyzed TCGA database to further confirm the expression levels of these hub genes in breast cancer. Our results showed that these regulators were significantly differentially expressed in breast cancer, which were consistent with GSE22358 dataset analysis. Furthermore, our analysis demonstrated that CEP55 was remarkably upregulated in the advanced stage of breast cancer compared to the stage I breast cancer sample and was significantly upregulated in triple-negative breast cancers (TNBC) compared to other types of breast cancers, including luminal and HER2-positive cancers, demonstrating CEP55 may have a regulatory role in TNBC. Finally, our results showed that CEP55 was the most highly expressed in Basal-like 1 TNBC and Basal-like 2 TNBC samples but the most lowly expressed in mesenchymal stem-like TNBC samples. Although more studies are still needed to understand the functions of key regulators in BC, this study provides useful information to understand the mechanisms underlying BC spinal metastases.

SKA3 promotes glioblastoma proliferation and invasion by enhancing the activation of Wnt/β-catenin signaling via modulation of the Akt/GSK-3β axis

Spindle and kinetochore-related complex subunit 3 (SKA3) is a key modulator of the progression of multiple tumor types. However, the involvement of SKA3 in glioblastoma (GBM) has not been well studied. The current study aimed to explore the role of SKA3 expression and the potential function of the protein in GBM. Our data showed that SKA3 expression was significantly up-regulated in GBM. Functional assays demonstrated that the knockdown of SKA3 impeded the proliferation, colony formation and invasion of GBM cells, while SKA3 overexpression produced the opposite effects. Further investigation revealed that SKA3 overexpression enhanced the activation of Wnt/β-catenin signaling, which was associated with the enhanced phosphorylation of Akt and glycogen synthase kinase-3β (GSK-3β). Notably, the inhibition of Akt markedly abrogated the SKA3 overexpression-induced promotion of Wnt/β-catenin signaling in GBM cells. Further, the inhibition of Wnt/β-catenin signaling markedly abrogated the SKA3 overexpression-induced promotion of tumor growth. In addition, the knockdown of SKA3 significantly retarded tumor formation and GBM progression in vivo. In summary, these data demonstrate that SKA3 exerts promotes tumor growth in GBM by enhancing the activation of Wnt/β-catenin signaling via modulation of the Akt/GSK-3β axis. This work highlights the pivotal role of SKA3/Akt/GSK-3β/Wnt/β-catenin signaling in the progression of GBM and suggests that SKA3 is an attractive therapeutic target with potential to be used to treat GBM.

KRT8 and KRT19, associated with EMT, are hypomethylated and overexpressed in lung adenocarcinoma and link to unfavorable prognosis

Background: Lung adenocarcinoma (LUAD) is the most common histological type of lung cancer. To date, the prognosis of patients with LUAD remains dismal. Methods: Three datasets were downloaded from the GEO database. Differentially expressed genes (DEGs) were obtained. FunRich was used to perform pathway enrichment analysis. Protein–protein interaction (PPI) networks were established and hub genes were obtained by Cytoscape software. GEPIA was utilized to conduct correlation and survival analysis. Upstream miRNAs of DEGs were predicted via miRNet database, and methylation status of promoters of DEGs was determined through UALCAN database. Results: A total of 375 DEGs, including 105 and 270 up-regulated and down-regulated genes in LUAD, were commonly appeared in three datasets. These DEGs were significantly enriched in mesenchymal-to-epithelial transition (MET) and epithelial-to-mesenchymal transition (EMT). About 8 up-regulated and 5 down-regulated DEGs were commonly appeared in EMT/MET-related gene set and the top 50 hub gene set. Among the 13 genes, increased expression of KRT8 and KRT19 indicated unfavorable prognosis whereas high expression of DCN and CXCL12 suggested favorable prognosis in LUAD. Correlation analysis showed that KRT8 (DCN) expression was linked to KRT19 (CXCL12) expression. Further analysis displayed that KRT8 and KRT19 could jointly forecast poor prognosis in LUAD. About 42 and 2 potential miRNAs were predicted to target KRT8 and KRT19, respectively. Moreover, methylation level analysis demonstrated that KRT8 and KRT19 were significantly hypomethylated in LUAD compared with normal controls. Conclusions: All these findings suggest that KRT8 and KRT19 are hypomethylated and overexpressed in LUAD and associated with unfavorable prognosis.

Spindle and kinetochore‑associated complex subunit 3 accelerates breast cancer cell proliferation and invasion through the regulation of Akt/Wnt/β-catenin signaling

PURPOSE

Spindle and kinetochore‑associated complex subunit 3 (SKA3) has recently been identified as a novel regulator of carcinogenesis in multiple types of cancers. However, the function and potential regulatory mechanisms of SKA3 in breast cancer remain poorly understood. The present study was designed to gain a detailed relevance of SKA3 in breast cancer.

METHODS

Expression of SKA3 in breast cancer was examined via real-time quantitative PCR, western blotting and immunohistochemistry analysis. Malignant behaviors of breast cancer cells were investigated via cell counting kit-8, cell apoptosis, and transwell invasion assays. The activity of Wnt/β-catenin signaling was monitored via luciferase reporter assay. The tumorigenicity of breast cancer cells in vivo was assessed via xenograft tumor assay.

RESULTS

SKA3 expression was elevated in breast cancer tissue and was correlated with shorter survival rates in breast cancer patients. Knockdown of SKA3 caused marked reductions in cellular proliferation and invasion in breast cancer cells, whereas SKA3 overexpression accelerated proliferation and invasion. Knockdown of SKA3 resulted in decreased Akt and glycogen synthase kinase-3β phosphorylation, and decreased expression of active β-catenin, which lead to the inactivation of Wnt/β-catenin signaling. Inhibition of Akt significantly reversed the SKA3 overexpression-induced activation of Wnt/β-catenin signaling. Inhibition of Wnt/β-catenin signaling markedly abrogated SKA3 overexpression-induced tumor-promotion effects, while re-activation of Wnt/β-catenin signaling significantly reversed SKA3 knockdown-mediated tumor-inhibition effects. Knockdown of SKA3 resulted in a significant decrease in breast cancer tumor formation in vivo.

CONCLUSIONS

SKA3 accelerates proliferation and invasion in breast cancer through the modulation of Akt/Wnt/β-catenin signaling.

Platelet isoform of phosphofructokinase promotes aerobic glycolysis and the progression of non‑small cell lung cancer

The platelet isoform of phosphofructokinase (PFKP) is a rate-limiting enzyme involved in glycolysis that serves an important role in various types of cancer. The aim of the present study was to explore the specific regulatory relationship between PFKP and non-small cell lung cancer (NSCLC) progression. PFKP expression in NSCLC tissues and corresponding adjacent tissues was detected using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and immunohistochemical analysis. PFKP expression in human bronchial epithelial cells (16HBE) and NSCLC cells (H1299, H23 and A549) was also detected using RT-qPCR. Cell proliferation was detected by Cell Counting Kit-8 and colony formation assays. Transwell invasion and wound healing assays, and flow cytometry were used to detect cell invasion, migration and apoptosis, respectively. The expression levels of glycolysis-associated enzymes (hexokinase-2, lactate dehydrogenase A and glucose transporter-1), epithelial-mesenchymal transition-related proteins (N-cadherin, vimentin and E-cadherin) and apoptosis-related proteins (caspase-3 and B-cell lymphoma-2) were detected by western blotting. Glucose uptake, lactate production and the adenosine trisphosphate/adenosine diphosphate ratio were measured using the corresponding kits. The results of the present study demonstrated that PFKP expression was upregulated in NSCLC tissues and cells, and PFKP expression was related to lymph node metastasis and histological grade. In addition, overexpression of PFKP inhibited cell apoptosis, and promoted proliferation, migration, invasion and glycolysis of H1299 cells, whereas knockdown of PFKP had the opposite effects. In conclusion, PFKP inhibited cell apoptosis, and promoted proliferation, migration, invasion and glycolysis of NSCLC cells; these findings may lay the foundation for novel treatments of NSCLC.

Screening and Identification of Potential Biomarkers in Hepatitis B Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis

Hepatocellular carcinoma (HCC) is one of the most lethal cancers globally. Hepatitis B virus (HBV) infection might cause chronic hepatitis and cirrhosis, leading to HCC. To screen prognostic genes and therapeutic targets for HCC by bioinformatics analysis and determine the mechanisms underlying HBV-related HCC, three high-throughput RNA-seq based raw datasets, namely GSE25599, GSE77509, and GSE94660, were obtained from the Gene Expression Omnibus database, and one RNA-seq raw dataset was acquired from The Cancer Genome Atlas (TCGA). Overall, 103 genes were up-regulated and 127 were down-regulated. A protein–protein interaction (PPI) network was established using Cytoscape software, and 12 pivotal genes were selected as hub genes. The 230 differentially expressed genes and 12 hub genes were subjected to functional and pathway enrichment analyses, and the results suggested that cell cycle, nuclear division, mitotic nuclear division, oocyte meiosis, retinol metabolism, and p53 signaling-related pathways play important roles in HBV-related HCC progression. Further, among the 12 hub genes, kinesin family member 11 (KIF11), TPX2 microtubule nucleation factor (TPX2), kinesin family member 20A (KIF20A), and cyclin B2 (CCNB2) were identified as independent prognostic genes by survival analysis and univariate and multivariate Cox regression analysis. These four genes showed higher expression levels in HCC than in normal tissue samples, as identified upon analyses with Oncomine. In addition, in comparison with normal tissues, the expression levels of KIF11, TPX2, KIF20A, and CCNB2 were higher in HBV-related HCC than in HCV-related HCC tissues. In conclusion, our results suggest that KIF11, TPX2, KIF20A, and CCNB2 might be involved in the carcinogenesis and development of HBV-related HCC. They can thus be used as independent prognostic genes and novel biomarkers for the diagnosis of HBV-related HCC and development of pertinent therapeutic strategies.

Identification of Spindle and Kinetochore-Associated Family Genes as Therapeutic Targets and Prognostic Biomarkers in Pancreas Ductal Adenocarcinoma Microenvironment

Aim

The role of spindle and kinetochore-associated (SKA) genes in tumorigenesis and cancer progression has been widely studied. However, so far, the oncogenic involvement of SKA family genes in pancreatic cancer and their prognostic potential remain unknown.

Methods

Here, we carried out a meta-analysis of the differential expression of SKA genes in normal and tumor tissue. Univariate and multivariate survival analyses were done to evaluate the correlation between SKA family gene expression and pancreas ductal adenocarcinoma (PDAC) prognosis. Joint-effect and stratified survival analysis as well as nomogram analysis were used to estimate the prognostic value of genes. The underlying regulatory and biological mechanisms were identified by Gene set enrichment analysis. Interaction between SKA prognosis-related genes and immune cell infiltration was assessed using the Tumor Immune Estimation Resource tool.

Results

We find that SKA1-3 are highly expressed in PDAC tissues relative to non-cancer tissues. Survival analysis revealed that high expression of SKA1 and SKA3 independently indicate poor prognosis but they are not associated with relapse-free survival. The prognostic value of SKA1 and SKA3 was further confirmed by the nomogram, joint-effect, and stratified survival analysis. Analysis of underlying mechanisms reveals that these genes influence cancer-related signaling pathways, kinases, miRNA, and E2F family genes. Notably, prognosis-related genes are inversely correlated with several immune cells infiltrating levels.

Conclusion

We find that SKA1 and SKA3 expression correlates with prognosis and immune cell infiltration in PDAC, highlighting their potential as pancreatic cancer prognostic biomarkers.

Targeting SKA3 suppresses the proliferation and chemoresistance of laryngeal squamous cell carcinoma via impairing PLK1-AKT axis-mediated glycolysis

Spindle and kinetochore-associated complex subunit 3 (SKA3) is a well-known regulator of chromosome separation and cell division, which plays an important role in cell proliferation. However, the mechanism of SKA3 regulating tumor proliferation via reprogramming metabolism is unknown. Here, SKA3 is identified as an oncogene in laryngeal squamous cell carcinoma (LSCC), and high levels of SKA3 are closely associated with malignant progression and poor prognosis. In vitro and in vivo experiments demonstrate that SKA3 promotes LSCC cell proliferation and chemoresistance through a novel role of reprogramming glycolytic metabolism. Further studies reveal the downstream mechanisms of SKA3, which can bind and stabilize polo-like kinase 1 (PLK1) protein via suppressing ubiquitin-mediated degradation. The accumulation of PLK1 activates AKT and thus upregulates glycolytic enzymes HK2, PFKFB3, and PDK1, resulting in enhancement of glycolysis. Furthermore, our data reveal that phosphorylation at Thr360 of SKA3 is critical for its binding to PLK1 and the increase in glycolysis. Collectively, the novel oncogenic signal axis "SKA3-PLK1-AKT" plays a critical role in the glycolysis of LSCC. SKA3 may serve as a prognostic biomarker and therapeutic target, providing a potential strategy for proliferation inhibition and chemosensitization in tumors, especially for LSCC patients with PLK1 inhibitor resistance.

Identifying of miR-98-5p/IGF1 axis contributes breast cancer progression using comprehensive bioinformatic analyses methods and experiments validation

BACKGROUND

Breast cancer (BC) is a huge health threat for women worldwide. Although numerous microRNAs (miRNA) have been found to be aberrantly expressed in BC, the construction of a comprehensive miRNA-messenger RNA (mRNA) network is still needed.

METHODS

Limma package was used to identify differentially expressed miRNAs (DEMs) in microarray datasets downloaded from GEO database. Genes targeted by DEMs were analyzed using mirTarBase. Gene Ontology and pathway enrichment analysis for these genes were performed at DAVID. Expression correlations of DEMs and target genes were analyzed at ENCORI. Based on these results, a miRNA-mRNA regulatory network was constructed.

RESULTS

A total of 17 overlapping DEMs were identified at these two microarray datasets. Expression of DEMs in BC tissues compared with normal tissues were further validated by ENCORI. By utilizing miRTarBase, a total of 167 target genes for DEMs were obtained. 10 hub genes (AKT1, MYC, VEGFA, CCND1, PTEN, IL6, CASP3, KRAS, IGF1, ESR1) were identified. Through analyzing the effects of hub genes on overall survival of BC patients and their expression correlation with miRNAs, we found hsa-miR-98-5p/IGF1 axis may play a crucial role in BC progression. The connections of hsa-miR-98-5p and IGF1 were further validated by luciferase activity reporter assay and functional assays.

CONCLUSIONS

In this work, a miRNA-mRNA network related to BC progression was built, and identified one important miRNA-mRNA axis in BC.

Histone Demethylase KDM5B as a Therapeutic Target for Cancer Therapy

Lysine-specific demethylase 5B (KDM5B/PLU1/JARID1B) is found to be overexpressed in numerous malignancies, including breast, lung, skin, liver, and prostate cancer. Identification of molecules targeting the KDM5B enzyme could be a potential lead in cancer research. Although many KDM5B inhibitors with promising outcomes have been developed so far, its further application in clinical practice is limited due to toxicity and lack of target specificity. Here, we summarize the significance of targeting KDM5B in anticancer therapy and report the molecular docking studies of some known anti-viral agents, decitabine, entecavir, abacavir, penciclovir, and 3-deazaneplanocin A in the catalytic domain JmjC of KDM5B. These studies show the repurposing potential of identified anti-viral agents in cancer therapy.

iRGD-targeted hybrid nanoparticles reverses multi-drug resistant to effectively combat liver cancer

The off-target delivery as well as multi-drug resistance (MDR) are generally recognised as two keys difficulties responsible for the poor performance of chemotherapy in clinical treatment of cancer. With the aim to address the problems, we herein constructed iRGD modified and lipid-coated silica (LSC) nanoparticles co-delivering Ca²⁺ channel siRNA and adriamycin (Adr) to reverse the MDR in liver cancer (LSC/R-A). The iRGD decoration was suggested to elevate the tumour accumulation of the drug delivery system (DDS). In addition, the introduction of Ca²⁺ channel siRNA was proved to reverse the MDR within the cells of cancer by regulation the T-type Ca²⁺ channels. Our results showed that decreased expression of T-type Ca²⁺ channels resulted in lowered cytosolic Ca²⁺ level responsible for the cell cycle arrest (at G0/G1 phase) as well as elevated cellular drug retention in HepG2/Adr. B in vitro/in vivo experiments revealed that LSC/R-A exerted highly elevated therapeutic outcome on HepG2/Adr, than administration of single siRNA or Adr.

Heparin-Binding Protein: A Novel Biomarker Linking Four Different Cardiovascular Diseases

Cardiovascular diseases are an important group of diseases that seriously affect quality of life. Thus, their treatment warrants further study. Heparin-binding protein (HBP) is a granulocyte protein derived from neutrophils. When an infection occurs, neutrophils release HBP, which can lead to elevated HBP levels in the blood. Therefore, HBP family members are said to be important indicators of infection. However, basic evidence is still lacking to confirm the possible relationship between HBP and cardiovascular diseases. Using bioinformatics methods, we investigated the role of the HBP network in normal hearts and hearts from patients with cardiovascular disease. First, we used the Open Targets database to obtain a list of HBP-encoding mRNAs related to atherosclerosis, myocarditis, myocardial infarction, and myocardial ischemia. Then, we constructed an HBP gene interaction network map using STRING. Clustering coefficients were calculated using Cytoscape, and MCODE was used for subnet analysis. Finally, the proposed interstitial network of HBPs was established and analyzed by Metascape enrichment analysis of the relevant signaling pathways. The aggregation coefficient of the HBP interaction network was higher among hearts with the four cardiovascular diseases, atherosclerosis (0.496), myocarditis (0.631), myocardial infarction (0.532), and myocardial ischemia (0.551), than in normal hearts. Metascape analysis showed that "NABA_MATRISOME_ASSOCIATED" was a typical pathway with the highest p value associated with epithelialization in all four diseases. Moreover, a large number of important HBPs were identified that may be significant for the treatment of these diseases. Therefore, HBPs do have a highly atopic connectivity network in cardiovascular diseases, and specific HBPs or signaling pathways may be used as targets for the development of new treatments for cardiovascular diseases.

A novel mRNA-miRNA-lncRNA competing endogenous RNA triple sub-network associated with prognosis of pancreatic cancer

Background: Recently, increasing evidence has uncovered the roles of mRNA-miRNA-lncRNA network in multiple human cancers. However, a systematic mRNA-miRNA-lncRNA network linked to pancreatic cancer prognosis is still absent. Methods: Differentially expressed genes (DEGs) were first identified by mining GSE16515 and GSE15471 datasets. DAVID database was utilized to conduct functional enrichment analysis. Protein-protein interaction (PPI) network was built using STRING database, and hub genes were identified by Cytoscape plug-in CytoHubba. Upstream miRNAs and lncRNAs of mRNAs were predicted by miRTarBase and miRNet, respectively. Expression, survival and correlation analysis for genes, miRNAs and lncRNAs were performed via GEPIA, Kaplan-Meier plotter and starBase. Results: 734 and 180 upregulated and downregulated significant DEGs were identified, respectively. Functional enrichment analysis revealed that they were significantly enriched in focal adhesion, pathways in cancer and metabolic pathways. According to node degree, hub genes in the PPI networks were screened, such as TGFB1 and ALB. Among the top 20 hub genes, 7 upregulated genes and 2 downregulated hub genes had significant prognostic values in pancreatic cancer. 33 miRNAs were predicted to target the 9 key genes. But only high expression of 8 miRNAs indicated favorable prognosis in pancreatic cancer. Then, 90 lncRNAs were predicted to potentially bind to the 8 miRNAs. SCAMP1, HCP5, MAL2 and LINC00511 were finally identified as key lncRNAs. By combination of results from expression, survival and correlation analysis demonstrated that MMP9/ITGB1-miR-29b-3p-HCP5 competing endogenous RNA (ceRNA) sub-network was linked to prognosis of pancreatic cancer. Conclusions: In a word, we established a novel mRNA-miRNA-lncRNA sub-network, among which each RNA may be utilized as a prognostic biomarker of pancreatic cancer.

Identification of key genes associated with the progression of intrahepatic cholangiocarcinoma using weighted gene co-expression network analysis

The present study aimed to identify the key genes that are associated with the progression of intrahepatic cholangiocarcinoma through weighted gene co-expression network analysis (WGCNA). A total of three gene datasets were downloaded from the Gene Expression Omnibus database, including GSE107943, GSE119336 and GSE26566. Differentially expressed genes (DEGs) between intrahepatic cholangiocarcinoma tissues and adjacent liver tissues were identified using GSE107943, while tissue specific genes between bile duct and liver tissues were identified using GSE26566. Following the removal of tissue-specific genes, real DEGs were used to construct the WGCNA to investigate the association between gene modules and clinical traits. Following functional analysis, pathway enrichment analysis and the construction of a protein-protein interaction (PPI) network were performed, hub genes were selected and their diagnostic value was verified in GSE119336 using a receiver operating characteristic curve. Finally, the protein levels of the hub genes were also verified in intrahepatic cholangiocarcinoma tissues. A total of 1,643 real DEGs were identified and used to construct the WGCNA. Additionally, a total of seven co-expressed gene modules were identified following WGCNA, while genes in brown and yellow modules were identified to be associated with multiple clinical traits (the number of clinical traits >3) and used as key modules. A total of 63 core key module genes were subsequently identified, and it was indicated that these genes were most enriched in the nucleus (Gene Ontology term) and the cell cycle pathway (Kyoto Encyclopedia of Genes and Genomes term). Finally, a total of eight genes, including cyclin B1, cell division cycle 20, cell division cycle associated 8, cyclin dependent kinase 1, centrosomal protein 55, kinesin family member 2C, DNA topoisomerase IIα and TPX2 microtubule nucleation factor, exhibited the highest score in PPI analysis and had a high diagnostic value for intrahepatic cholangiocarcinoma. In addition, the protein levels of these genes were also revealed to be increased in most intrahepatic cholangiocarcinoma tissues. These eight genes may be used as novel biomarkers for the diagnosis of intrahepatic cholangiocarcinoma.

Folic acid decorated metal-organic frameworks loaded with doxorubicin for tumor-targeted chemotherapy of osteosarcoma

Effective cancer therapy usually requires the assistance of well-designed drug carriers. In order to increase the drug accumulation to tumor tissue as well as to reduce the side effects of drug carriers, the hybrid drug delivery system (DDS) was developed by integrating folic acid (FA) and a metal-organic framework (MOF). The anticancer drug doxorubicin (DOX) was preloaded into the MOF nanoparticles during the synthesis process of the MOF nanoparticles. After surface modification with FA, the resulting FA/MOF/DOX nanoparticles were capable of serving as a biocompatible osteosarcoma targeting a DDS to enhance the chemotherapy of osteosarcoma. The dynamic light scattering method revealed that the obtained FA/MOF/DOX nanoparticles were particles with a size around 100 nm. Moreover, FA/MOF/DOX nanoparticles could enhance the delivery efficacy of DOX into MG63 (human osteosarcoma) cells as compared to FA free nanoparticles (MOF/DOX), in which a folate receptor (FR) might be involved. It was worth mentioning that in vitro [methylthio tetrazole (MTT) study in the MG63 cells] and in vivo (anticancer study in the MG63 xenograft model) assays both revealed that FA/MOF/DOX nanoparticles possessed stronger anticancer capability than free DOX or MOF/DOX nanoparticles.

SKA1/2/3 serves as a biomarker for poor prognosis in human lung adenocarcinoma

Background

Spindle and kinetochore associated complex subunit 1/2/3 (SKA1/2/3), which stabilized spindle microtubules attaching to kinetochore (KT) in the middle stage of mitosis, were dysregulated, and closely related to prognosis in several malignant tumors. Nevertheless, the potential clinical value of SKA1/2/3, especially in terms of prognosis and development of NSCLC, had not been fully elucidated.

Methods

ONCOMINE, GEPIA, UALCAN, TCGA, STRING and other databases were used to analyze the expression of SKA1/2/3 in patients with lung adenocarcinoma (LUAD) and its clinical value, and to explore the possible regulatory mechanism of SKA in the occurrence and development of LUAD.

Results

In patients with LUAD, SKA1/2/3 mRNA expression level was significantly up-regulated, and AUC was 0.9558, 0.7034 and 0.9775, respectively. Increased SKA 1/2/3 expression was associated with smoking, tissue typing, and poor prognosis in LUAD patients. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) showed that SKA1/2/3 was mainly enriched in DNA replication, cell cycle, homologous recombination, p53 signaling pathway, etc. Hub genes in protein-protein interactions are CDK1, BUB1, CCNA2, CDC20, CCNB2, CCNB1, BUB1B, AURKB, TOP2A and MAD2L1. Hub gene expression in LUAD is increased, and its increased expression is related to poor prognosis of LUAD patients. Finally, the expression of SKA1/2/3 and its correlation with clinicopathological features were verified in 30 clinical LUAD samples.

Conclusions

SKA1/2/3 may serve as a potential prognostic biomarker and target for LUAD. In addition, SKA 1/2/3 may affect the prognosis of LUAD through DNA replication, cell cycle, homologous recombination and p53 signaling pathway.