High EGFR_1 Inside-Out Activated Inflammation-Induced Motility through SLC2A1-CCNB2-HMMR-KIF11-NUSAP1-PRC1-UBE2C

Mitotic Functions and Characters of KIF11 in Cancers

Mitosis mediates the accurate separation of daughter cells, and abnormalities are closely related to cancer progression. KIF11, a member of the kinesin family, plays a vital role in the formation and maintenance of the mitotic spindle. Recently, an increasing quantity of data have demonstrated the upregulated expression of KIF11 in various cancers, promoting the emergence and progression of cancers. This suggests the great potential of KIF11 as a prognostic biomarker and therapeutic target. However, the molecular mechanisms of KIF11 in cancers have not been systematically summarized. Therefore, we first discuss the functions of the protein encoded by KIF11 during mitosis and connect the abnormal expression of KIF11 with its clinical significance. Then, we elucidate the mechanism of KIF11 to promote various hallmarks of cancers. Finally, we provide an overview of KIF11 inhibitors and outline areas for future work.

HMMR associates with immune infiltrates and acts as a prognostic biomaker in lung adenocarcinoma

BACKGROUND

To explore the expression of hyaluronan mediated motility receptor (HMMR) in lung adenocarcinoma (LUAD) and its relationship with clinicopathological features and tumor-infiltrating is not clear.

METHODS

The expression of HMMR in Cancer Cell Line Encyclopedia (CCLE) and The Cancer Genome Atlas (TCGA)-LUAD. TCGA was employed to examine the relationship between the clinicopathological characteristics and HMMR expression and the LUAD patients' prognosis. Tumor Immune Estimation Resource (TIMER)database was employed to analyze the relationship between immune infiltration and HMMR. Gene Set Enrichment Analysis was explored through gene enrichment. Gene Expression Omnibus (GEO) data and our hospital data were utilized to confirm the findings.

RESULTS

The expression level of HMMR in lung adenocarcinoma tissue and cells was greater than that in the normal group, which was linked to clinical stage, smoking history, and recurrence, and could increase the progression or recurrence of LUAD. Patients in the pathological grade had a significant expression of HMMR in moderately differentiated LUAD tissues. In addition, HMMR has an impact on LUAD patients' overall survival rate [P = 9.5e-06; hazard ratio (HR) = 2]. The level of HMMR expression in LUAD was significantly linked to neutrophils, CD8+T, and CD4+T cells. TMB analysis showed that HMMR could also affect the tumor microenvironment in LUAD. HMMR might be employed as an independent predictive biomarker of LUAD, according to a multivariate COX regression analysis. The findings of GSEA analysis showed that the samples with high HMMR expression levels were rich in cell cycle, cell metabolism, and DNA replication. The analysis results of GSE31210 data are basically consistent with those of TCGA-LUAD.

CONCLUSIONS

It is suggested that HMMR has an effect on the occurrence and development of lung adenocarcinoma. Besides, HMMR is also linked to the level of immune infiltration of neutrophils, CD8+T cells, and CD4+T cells and LUAD patients' prognosis. HMMR was suggested to be utilized as a biomarker or therapeutic target to judge the prognosis and immune infiltration of LUAD.

Network Pharmacology and Comparative Transcriptome Reveals Biotargets and Mechanisms of Curcumol Treating Lung Adenocarcinoma Patients With COVID-19

The coronavirus disease 2019 (COVID-19) pandemic has led to 4,255,892 deaths worldwide. Although COVID-19 vaccines are available, mutant forms of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have reduced the effectiveness of vaccines. Patients with cancer are more vulnerable to COVID-19 than patients without cancer. Identification of new drugs to treat COVID-19 could reduce mortality rate, and traditional Chinese Medicine(TCM) has shown potential in COVID-19 treatment. In this study, we focused on lung adenocarcinoma (LUAD) patients with COVID-19. We aimed to investigate the use of curcumol, a TCM, to treat LUAD patients with COVID-19, using network pharmacology and systematic bioinformatics analysis. The results showed that LUAD and patients with COVID-19 share a cluster of common deregulated targets. The network pharmacology analysis identified seven core targets (namely, AURKA, CDK1, CCNB1, CCNB2, CCNE1, CCNE2, and TTK) of curcumol in patients with COVID-19 and LUAD. Clinicopathological analysis of these targets demonstrated that the expression of these targets is associated with poor patient survival rates. The bioinformatics analysis further highlighted the involvement of this target cluster in DNA damage response, chromosome stability, and pathogenesis of LUAD. More importantly, these targets influence cell-signaling associated with the Warburg effect, which supports SARS-CoV-2 replication and inflammatory response. Comparative transcriptomic analysis on in vitro LUAD cell further validated the effect of curcumol for treating LUAD through the control of cell cycle and DNA damage response. This study supports the earlier findings that curcumol is a potential treatment for patients with LUAD and COVID-19.

Immune Response Is Key to Genetic Mechanisms of SARS-CoV-2 Infection With Psychiatric Disorders Based on Differential Gene Expression Pattern Analysis

Existing evidence demonstrates that coronavirus disease 2019 (COVID-19) leads to psychiatric illness, despite its main clinical manifestations affecting the respiratory system. People with mental disorders are more susceptible to COVID-19 than individuals without coexisting mental health disorders, with significantly higher rates of severe illness and mortality in this population. The incidence of new psychiatric diagnoses after infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is also remarkably high. SARS-CoV-2 has been reported to use angiotensin-converting enzyme-2 (ACE2) as a receptor for infecting susceptible cells and is expressed in various tissues, including brain tissue. Thus, there is an urgent need to investigate the mechanism linking psychiatric disorders to COVID-19. Using a data set of peripheral blood cells from patients with COVID-19, we compared this to data sets of whole blood collected from patients with psychiatric disorders and used bioinformatics and systems biology approaches to identify genetic links. We found a large number of overlapping immune-related genes between patients infected with SARS-CoV-2 and differentially expressed genes of bipolar disorder (BD), schizophrenia (SZ), and late-onset major depressive disorder (LOD). Many pathways closely related to inflammatory responses, such as MAPK, PPAR, and TGF-β signaling pathways, were observed by enrichment analysis of common differentially expressed genes (DEGs). We also performed a comprehensive analysis of protein-protein interaction network and gene regulation networks. Chemical-protein interaction networks and drug prediction were used to screen potential pharmacologic therapies. We hope that by elucidating the relationship between the pathogenetic processes and genetic mechanisms of infection with SARS-CoV-2 with psychiatric disorders, it will lead to innovative strategies for future research and treatment of psychiatric disorders linked to COVID-19.

Development of a novel embryonic germline gene-related prognostic model of lung adenocarcinoma

Background

Emerging evidence implicates the correlation of embryonic germline genes with the tumor progress and patient's outcome. However, the prognostic value of these genes in lung adenocarcinoma (LUAD) has not been fully studied. Here we systematically evaluated this issue, and constructed a novel signature and a nomogram associated with embryonic germline genes for predicting the outcomes of lung adenocarcinoma.

Methods

The LUAD cohorts retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database were used as training set and testing set, respectively. The embryonic germline genes were downloaded from the website https://venn.lodder.dev. Then, the differentially expressed embryonic germline genes (DEGGs) between the tumor and normal samples were identified by limma package. The functional enrichment and pathway analyses were also performed by clusterProfiler package. The prognostic model was constructed by the least absolute shrinkage and selection operator (LASSO)-Cox regression method. Survival and Receiver Operating Characteristic (ROC) analyses were performed to validate the model using training set and four testing GEO datasets. Finally, a prognostic nomogram based on the signature genes was constructed using multivariate regression method.

Results

Among the identified 269 DEGGs, 249 were up-regulated and 20 were down-regulated. GO and KEGG analyses revealed that these DEGGs were mainly enriched in the process of cell proliferation and DNA damage repair. Then, 103 DEGGs with prognostic value were identified by univariate Cox regression and further filtered by LASSO method. The resulting sixteen DEGGs were included in step multivariate Cox regression and an eleven embryonic germline gene related signature (EGRS) was constructed. The model could robustly stratify the LUAD patients into high-risk and low-risk groups in both training and testing sets, and low-risk patients had much better outcomes. The multi-ROC analysis also showed that the EGRS model had the best predictive efficacy compared with other common clinicopathological factors. The EGRS model also showed robust predictive ability in four independent external datasets, and the area under curve (AUC) was 0.726 (GSE30219), 0.764 (GSE50081), 0.657 (GSE37745) and 0.668 (GSE72094). More importantly, the expression level of some genes in EGRS has a significant correlation with the progression of LUAD clinicopathology, suggesting these genes might play an important role in the progression of LUAD. Finally, based on EGRS genes, we built and calibrated a nomogram for conveniently evaluating patients' outcomes.

Cyclin B2 (CCNB2) Stimulates the Proliferation of Triple-Negative Breast Cancer (TNBC) Cells In Vitro and In Vivo

Triple-negative breast cancer (TNBC) is the most aggressive type of breast cancer. Currently, targeting therapy makes great advances for the treatment of TNBC, whereas more effective therapeutic targets are urgently needed. Cyclin B2 (CCNB2), which belongs to B-type cyclins, is known as a cell cycle regulator. CCNB2 is synthesized at G1 phase in cancer cells and downregulated at anaphase. The defects of CCNB2 led to the abnormal cell cycle and tumorigenesis. Though there are wide effects of CCNB2 on multiple types of tumors, the potential role of CCNB2 in TNBC progression is still unclear. Herein, we found that CCNB2 was highly expressed in human TNBC tissues and correlated with the prognosis and clinical pathological features including tumor size (p = 0.022^∗) and pTNM stage (p = 0.021^∗) of patients with TNBC. CCNB2 could promote the proliferation of TNBC cells in vitro and in mice. Our findings therefore confirmed the involvement of CCNB2 in TNBC progression and provided the evidence that CCNB2 could serve as a promising molecular target of TNBC.

Development of an Aerobic Glycolysis Index for Predicting the Sorafenib Sensitivity and Prognosis of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a deadly tumor with high heterogeneity. Aerobic glycolysis is a common indicator of tumor growth and plays a key role in tumorigenesis. Heterogeneity in distinct metabolic pathways can be used to stratify HCC into clinically relevant subgroups, but these have not yet been well-established. In this study, we constructed a model called aerobic glycolysis index (AGI) as a marker of aerobic glycolysis using genomic data of hepatocellular carcinoma from The Cancer Genome Atlas (TCGA) project. Our results showed that this parameter inferred enhanced aerobic glycolysis activity in tumor tissues. Furthermore, high AGI is associated with poor tumor differentiation and advanced stages and could predict poor prognosis including reduced overall survival and disease-free survival. More importantly, the AGI could accurately predict tumor sensitivity to Sorafenib therapy. Therefore, the AGI may be a promising biomarker that can accurately stratify patients and improve their treatment efficacy.

A Systematic Analysis of Dysregulated Long Non-Coding RNAs/microRNAs/mRNAs in Lung Squamous Cell Carcinoma

BACKGROUND

Lung squamous cell carcinoma (LUSC) accounts up for approximately 30% of all lung cancers with a high mortality. The study was aimed at finding genes critical in the diagnosis and prognosis of LUSC.

MATERIALS AND METHODS

The differentially expressed (DE) genes (DEGs) and DE lncRNAs (DELs) from 501 LUSC and 49 normal lung tissues, and DE miRNAs (DEMs) from 478 LUSC and 45 normal lung tissues were respectively obtained via the TCGA database. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and co-expression network analyses were performed. Survival analysis and receiver operating characteristic curve of hub mRNAs were also analyzed. Competitive endogenous RNA networks of lncRNAs, miRNAs and mRNAs were constructed.

RESULTS

A total of 5747 DEGs, 378 DEMs and 3141 DELs in LUSC were identified in LUSC. The DEGs including AUARK, CDK1, KIF11 and EXO1 were proven to be significant metastatic indicators in LUSC, and 2 DEGs were significantly associated with the survival in LUSC patients. Some genes might have connections with many other gene nodes through a co-expression network. Four lncRNAs, 2 mRNAs and 2 miRNAs were identified as the candidates for the competitive miRNA-mRNA-lncRNA network and might serve as prognostic markers in LUSC.

CONCLUSIONS

We identified the differentially expressed lncRNAs, miRNAs and mRNAs in LUSC, providing further insights into the molecular mechanism of LUSC tumorigenesis and the potential prognostic biomarkers or therapeutic targets for LUSC.

The metabolic syndrome modifies the mRNA expression profile of extracellular vesicles derived from porcine mesenchymal stem cells

BACKGROUND

Mesenchymal stem cells (MSCs) perform paracrine functions by releasing extracellular vesicles (EVs) containing microRNA, mRNA, and proteins. We investigated the mRNA content of EVs in metabolic syndrome (MetS) and tested hypothesis that comorbidities interfere with the paracrine functionality of MSCs.

METHODS

Mesenchymal stem cells were collected from swine abdominal adipose tissue after 16 weeks of a low- (Lean) or high-calorie (MetS) diet (n = 5 each). We used next-generation mRNAs sequencing to identify mRNAs enriched and depleted in Lean- or MetS-EVs compared to the parent MSCs.

RESULTS

We found 88 and 130 mRNAs enriched in Lean-EVs and MetS-EVs, respectively, of which only eight were common genes encoding proteins related to the nucleus, endoplasmic reticulum, and membrane fraction. Lean-EVs were enriched with mRNAs primarily involved in transcription regulation and the transforming growth factor (TGF)-β signaling pathway, but devoid of genes related to regulation of inflammation. In contrast, MetS-EVs contained mRNAs involved in translational regulation and modulation of inflammation mediated by chemokines and cytokines, but lacked mRNAs related to TGF-β signaling. mRNAs enriched in EVs have the potential to target a significant proportion of genes enriched in EVs, but only 4% microRNA target genes overlap between Lean- and MetS-EVs. Co-culture with MetS-EVs also increased renal tubular cell inflammation in-vitro.

CONCLUSIONS

Metabolic syndrome may affect immunomodulatory function of porcine MSCs by modifying mRNA profiles of the EVs that they produce and post-transcriptional regulation. These observations may have important implications for cell-based therapy, and support development of strategies to improve the efficacy of MSCs and their EVs.

Human ex vivo prostate tissue model system identifies ING3 as an oncoprotein

BACKGROUND

Although the founding members of the INhibitor of Growth (ING) family of histone mark readers, ING1 and ING2, were defined as tumour suppressors in animal models, the role of other ING proteins in cellular proliferation and cancer progression is unclear.

METHODS

We transduced ex vivo benign prostate hyperplasia tissues with inducible lentiviral particles to express ING proteins. Proliferation was assessed by H3S10phos immunohistochemistry (IHC). The expression of ING3 was assessed by IHC on a human prostate cancer tissue microarray (TMA). Gene expression was measured by DNA microarray and validated by real-time qPCR.

RESULTS

We found that ING3 stimulates cellular proliferation in ex vivo tissues, suggesting that ING3 could be oncogenic. Indeed, ING3 overexpression transformed normal human dermal fibroblasts. We observed elevated levels of ING3 in prostate cancer samples, which correlated with poorer patient survival. Consistent with an oncogenic role, gene-silencing experiments revealed that ING3 is required for the proliferation of breast, ovarian, and prostate cancer cells. Finally, ING3 controls the expression of an intricate network of cell cycle genes by associating with chromatin modifiers and the H3K4me3 mark at transcriptional start sites.

CONCLUSIONS

Our investigations create a shift in the prevailing view that ING proteins are tumour suppressors and redefine ING3 as an oncoprotein.