Identification of Core Prognosis-Related Candidate Genes in Cervical Cancer via Integrated Bioinformatical Analysis

Identification of Crucial Genes and Signaling Pathways in Alectinib-Resistant Lung Adenocarcinoma Using Bioinformatic Analysis

Alectinib, a second-generation anaplastic lymphoma kinase (ALK) inhibitor, has been shown to be effective for patients with ALK-positive non-small cell lung cancer (NSCLC). However, alectinib resistance is a serious problem worldwide. To the best of our knowledge, little information is available on its molecular mechanisms using the Gene Expression Omnibus (GEO) database. In this study, the differentially expressed genes (DEGs) were selected from the gene expression profile GSE73167 between parental and alectinib-resistant human lung adenocarcinoma (LUAD) cell samples. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) annotation enrichment analyses were conducted using Database for Annotation, Visualization and Integrated Discovery (DAVID). The construction of protein-protein interaction (PPI) network was performed to visualize DEGs. The hub genes were extracted based on the analysis of the PPI network using plug-in cytoHubba of Cytoscape software. The functional roles of the key genes were investigated using Gene Expression Profiling Interactive Analysis (GEPIA), University of Alabama at Birmingham Cancer (UALCAN), Gene Set Enrichment Analysis (GSEA), and Tumor Immune Estimation Resource (TIMER) analysis. The networks of kinase, miRNA, and transcription-factor targets of SFTPD were explored using LinkedOmics. The drug sensitivity analysis of SFTPD was analyzed using the RNAactDrug database. Results showed a total of 144 DEGs were identified. Five hub genes were extracted, including mucin 5B (MUC5B), surfactant protein D (SFTPD), deleted in malignant brain tumors 1 (DMBT1), surfactant protein A2 (SFTPA2), and trefoil factor 3 (TFF3). The survival analysis using GEPIA displayed that low expression of SFTPD had a significantly negative effect on the prognosis of patients with LUAD. GSEA revealed that low expression of SFTPD was positively correlated with the pathways associated with drug resistance, such as DNA replication, cell cycle, drug metabolism, and DNA damage repair, including mismatch repair (MMR), base excision repair (BER), homologous recombination (HR), and nucleotide excision repair (NER). The SFTPD expression was negatively correlated with the drug sensitivity of alectinib according to RNAactDrug database. The expression of SFTPD was further validated in parental H3122 cells and alectinib-resistant H3122 cells by quantitative reverse transcription PCR (RT-qPCR). In conclusion, our study found that the five hub genes, especially low expression of SFTPD, are closely related to alectinib resistance in patients with LUAD.

Recent Updates on Oncogenic Signaling of Aurora Kinases in Chemosensitive, Chemoresistant Cancers: Novel Medicinal Chemistry Approaches for Targeting Aurora Kinases

The Aurora Kinase family (AKI) is composed of serine-threonine protein kinases involved in the modulation of the cell cycle and mitosis. These kinases are required for regulating the adherence of hereditary-related data. Members of this family can be categorized into aurora kinase A (Ark-A), aurora kinase B (Ark-B), and aurora kinase C (Ark-C), consisting of highly conserved threonine protein kinases. These kinases can modulate cell processes such as spindle assembly, checkpoint pathway, and cytokinesis during cell division. The main aim of this review is to explore recent updates on the oncogenic signaling of aurora kinases in chemosensitive/chemoresistant cancers and to explore the various medicinal chemistry approaches to target these kinases. We searched Pubmed, Scopus, NLM, Pubchem, and Relemed to obtain information pertinent to the updated signaling role of aurora kinases and medicinal chemistry approaches and discussed the recently updated roles of each aurora kinases and their downstream signaling cascades in the progression of several chemosensitive/chemoresistant cancers; subsequently, we discussed the natural products (scoulerine, Corynoline, Hesperidin Jadomycin-B, fisetin), and synthetic, medicinal chemistry molecules as aurora kinase inhibitors (AKIs). Several natural products' efficacy was explained as AKIs in chemosensitization and chemoresistant cancers. For instance, novel triazole molecules have been used against gastric cancer, whereas cyanopyridines are used against colorectal cancer and trifluoroacetate derivatives could be used for esophageal cancer. Furthermore, quinolone hydrazine derivatives can be used to target breast cancer and cervical cancer. In contrast, the indole derivatives can be preferred to target oral cancer whereas thiosemicarbazone-indole could be used against prostate cancer, as reported in an earlier investigation against cancerous cells. Moreover, these chemical derivatives can be examined as AKIs through preclinical studies. In addition, the synthesis of novel AKIs through these medicinal chemistry substrates in the laboratory using in silico and synthetic routes could be beneficial to develop prospective novel AKIs to target chemoresistant cancers. This study is beneficial to oncologists, chemists, and medicinal chemists to explore novel chemical moiety synthesis to target specifically the peptide sequences of aurora kinases in several chemoresistant cancer cell types.

Network-based drug repurposing for HPV-associated cervical cancer

In women, cervical cancer (CC) is the fourth most common cancer around the world with average cases of 604,000 and 342,000 deaths per year. Approximately 50% of high-grade CC are attributed to human papillomavirus (HPV) types 16 and 18. Chances of CC in HPV-positive patients are 6 times more than HPV-negative patients which demands timely and effective treatment. Repurposing of drugs is considered a viable approach to drug discovery which makes use of existing drugs, thus potentially reducing the time and costs associated with de-novo drug discovery. In this study, we present an integrative drug repurposing framework based on a systems biology-enabled network medicine platform. First, we built an HPV-induced CC protein interaction network named HPV2C following the CC signatures defined by the omics dataset, obtained from GEO database. Second, the drug target interaction (DTI) data obtained from DrugBank, and related databases was used to model the DTI network followed by drug target network proximity analysis of HPV-host associated key targets and DTIs in the human protein interactome. This analysis identified 142 potential anti-HPV repurposable drugs to target HPV induced CC pathways. Third, as per the literature survey 51 of the predicted drugs are already used for CC and 33 of the remaining drugs have anti-viral activity. Gene set enrichment analysis of potential drugs in drug-gene signatures and in HPV-induced CC-specific transcriptomic data in human cell lines additionally validated the predictions. Finally, 13 drug combinations were found using a network based on overlapping exposure. To summarize, the study provides effective network-based technique to quickly identify suitable repurposable drugs and drug combinations that target HPV-associated CC.

Bioinformatics Screening of Potential Biomarkers from mRNA Expression Profiles to Discover Drug Targets and Agents for Cervical Cancer

Bioinformatics analysis has been playing a vital role in identifying potential genomic biomarkers more accurately from an enormous number of candidates by reducing time and cost compared to the wet-lab-based experimental procedures for disease diagnosis, prognosis, and therapies. Cervical cancer (CC) is one of the most malignant diseases seen in women worldwide. This study aimed at identifying potential key genes (KGs), highlighting their functions, signaling pathways, and candidate drugs for CC diagnosis and targeting therapies. Four publicly available microarray datasets of CC were analyzed for identifying differentially expressed genes (DEGs) by the LIMMA approach through GEO2R online tool. We identified 116 common DEGs (cDEGs) that were utilized to identify seven KGs (AURKA, BRCA1, CCNB1, CDK1, MCM2, NCAPG2, and TOP2A) by the protein–protein interaction (PPI) network analysis. The GO functional and KEGG pathway enrichment analyses of KGs revealed some important functions and signaling pathways that were significantly associated with CC infections. The interaction network analysis identified four TFs proteins and two miRNAs as the key transcriptional and post-transcriptional regulators of KGs. Considering seven KGs-based proteins, four key TFs proteins, and already published top-ranked seven KGs-based proteins (where five KGs were common with our proposed seven KGs) as drug target receptors, we performed their docking analysis with the 80 meta-drug agents that were already published by different reputed journals as CC drugs. We found Paclitaxel, Vinorelbine, Vincristine, Docetaxel, Everolimus, Temsirolimus, and Cabazitaxel as the top-ranked seven candidate drugs. Finally, we investigated the binding stability of the top-ranked three drugs (Paclitaxel, Vincristine, Vinorelbine) by using 100 ns MD-based MM-PBSA simulations with the three top-ranked proposed receptors (AURKA, CDK1, TOP2A) and observed their stable performance. Therefore, the proposed drugs might play a vital role in the treatment against CC.

Identification of Key Pathways and Establishment of a Seven-Gene Prognostic Signature in Cervical Cancer

Cervical cancer (CC) remains high morbidity and mortality. We aimed to identify critical pathways underlying cervical carcinogenesis and establish a prognostic signature. Six datasets from the gene expression omnibus (GEO) database were used to screen the differentially expressed genes (DEGs) between CC and normal tissues. We used the unions of the DEGs to perform functional analysis. The 108 overlapped DEGs were analyzed to determine a prognostic signature by Cox regression and Lasso analysis based on The Cancer Genome Atlas (TCGA) database. Gene Set Enrichment Analysis (GSEA) and Immune Cell Abundance Identifier (ImmuCellAI) were used to determine the relationships between the signature and biological functions. The PI3K-Akt signaling pathway, the Ras signaling pathway, and the viral carcinogenesis pathway may be critical for CC development. We identified seven genes (PLOD2, DSG2, SPP1, CXCL8, MCM5, HLTF, and KLF4) to construct a risk score formula. Survival analysis showed that the high-risk group indicated a worse prognosis than the low-risk group (p < 0.0001). The AUC of the prognostic signature was 0.7449, 0.7641, and 0.8146 at 1, 3, and 5 years. We also identified that the signature is an independent prognostic factor. GSEA showed five pathways were relevant to the signature, such as the adherens junction pathway. The signature also affected the abundances of various types of immune cells, such as B cell, CD4+ T cell, and CD8+ T cell. Further, we found that SPP1 was co-expressed with HK3, CD163, CCL3, CLEC5A, MMP8, TREM1, OLR1, and TREM2. The results of Gene Ontology analysis showed that SPP1 and its co-expressed related proteins mainly affected metabolic process, multicellular organismal process, cell communication, cell proliferation, protein binding, and transporter activity. In conclusion, the present study explored the key pathways for CC development and the seven-gene signature can effectively make the prognosis evaluation of CC patients.

Prospero homeobox 1 promotes proliferation, migration, and invasion of osteosarcoma cells and its clinical significance

Osteosarcoma (OS) is the most common primary malignant bone tumor. Prospero homeobox 1 (PROX1) is a key transcription factor involved in some cancers, but the role of PROX1 in OS is unclear. This study aimed to explore the clinical and biology significance of PROX1 in OS. Fifty-four OS tissues and matched nontumor tissues were collected to explore the relationship between PROX1 expression and clinical characteristics and prognosis. qRT-PCR and immunohistochemistry were used to investigate the expression patterns of PROX1 in OS tissues and cells. CCK-8, wound healing, and transwell assays were used to detect the effects of PROX1 on the proliferation, migration, and invasion of OS cells. Transcriptome sequencing, bioinformatics analysis and qRT-PCR were used to explore the regulatory network of PROX1. PROX1 was significantly higher in OS tissues and cells compared to normal tissues and cell lines. In OS patients, high expression of PROX1 was associated with Enneking stage (P < 0.001) and M classification (P < 0.001). High PROX1 expression predicted a poorer overall survival (P = 0.0047). Compared with untreated cells, OS cells overexpressing PROX1 showed higher proliferation, migration, and invasion abilities, while knockdown of PROX1 suppressed these abilities. The results of Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis revealed that the down regulated genes were mainly enriched in TNF signaling pathway, MAPK signaling pathway, and neuroactive ligand-receptor interaction. High PROX1 expression was significantly associated with poor overall survival in OS patients. PROX1 may be a promising prognostic marker and therapeutic target for OS patients.

Whole-exome sequencing of rectal cancer identifies locally recurrent mutations in the Wnt pathway

Locally recurrent rectal cancer (LRRC) leads to a poor prognosis and appears as a clinically predominant pattern of failure. In this research, whole-exome sequencing (WES) was performed on 21 samples from 8 patients to search for the molecular mechanisms of LRRC. The data was analyzed by bioinformatics. Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) were performed to validate the candidate genes. Immunohistochemistry was used to detect the protein expression of LEF1 and CyclinD1 in LRRC, primary rectal cancer (PRC), and non-recurrent rectal cancer (NRRC) specimens. The results showed that LRRC, PRC, and NRRC had 668, 794, and 190 specific genes, respectively.

FGFR1 and MYC have copy number variants (CNVs) in PRC and LRRC, respectively. LRRC specific genes were mainly enriched in positive regulation of transcription from RNA polymerase II promoter, plasma membrane, and ATP binding. The specific signaling pathways of LRRC were Wnt signaling pathway, gap junction, and glucagon signaling pathway, etc. The transcriptional and translational expression levels of genes including NFATC1, PRICKLE1, SOX17, and WNT6 related to Wnt signaling pathway were higher in rectal cancer (READ) tissues than normal rectal tissues. The PRICKLE1 mutation (c.C875T) and WNT6 mutation (c.G629A) were predicted as “D (deleterious)”. Expression levels of LEF1 and cytokinin D1 proteins: LRRC > PRC > NRRC > normal rectal tissue. Gene variants in the Wnt signaling pathway may be critical for the development of LRRC. The present study may provide a basis for the prediction of LRRC and the development of new therapeutic drugs.

Prioritizing the candidate genes related to cervical cancer using the moment of inertia tensor

It is well known that cervical cancer poses the fourth most malignancy threat to women worldwide among all cancer types. There is a tremendous improvement in realizing the underlying molecular associations in cervical cancer. Several studies reported pieces of evidence for the involvement of various genes in the disease progression. However, with the ever-evolving bioinformatics tools, there has been an upsurge in predicting numerous genes responsible for cervical cancer progression and making it highly complex to target the genes for further evaluation. In this article, we prioritized the candidate genes based on the sequence similarity analysis with known cancer genes. For this purpose, we used the concept of the moment of inertia tensor, which reveals the similarities between the protein sequences more efficiently. Tensor for moment of inertia explores the similarity of the protein sequences based on the physicochemical properties of amino acids. From our analysis, we obtained 14 candidate cervical cancer genes, which are highly similar to known cervical cancer genes. Further, we analyzed the GO terms and prioritized these genes based on the number of hits with biological process, molecular functions, and their involvement in KEGG pathways. We also discussed the evidence-based involvement of the prioritized genes in other cancers and listed the available drugs for those genes.

Paeonol prevents migration and invasion, and promotes apoptosis of cervical cancer cells by inhibiting 5‑lipoxygenase

Cervical cancer is a common public health issue with high morbidity worldwide. Paeonol (Pae) has been recognized as a traditional Chinese medicine used for the treatment of various cancer types. However, whether Pae could exert a protective effect on cervical cancer remains to be investigated. The aim of the present study was to explore the role of Pae in cervical cancer cells and identify the potential mechanism. Cell Counting Kit‑8 and colony‑formation assays were conducted to test the proliferation of HeLa cells. Additionally, wound healing and transwell assays were used to detect the migratory and invasive abilities of cells. The plasmid that overexpressed 5‑lipoxygenase (5‑LO) or control vector was constructed and transfected into the cells. Subsequently, flow cytometry was used to monitor the apoptotic rate of cells. The expression levels of apoptosis‑associated proteins and 5‑LO were detected using western blot analysis. Reverse transcription‑quantitative PCR analysis detected the expression of 5‑LO. Pae inhibited the proliferation, invasion and migration of HeLa cells, promoted cell apoptosis and downregulated the expression of 5‑LO. Overexpression of 5‑LO, however, attenuated these effects. Thus, Pae could inhibit the proliferation, migration and invasion, as well as promote apoptosis of HeLa cells by regulating the expression of 5‑LO.

Identification of an immune-based mRNA-lncRNA signature for overall survival in cervical squamous cell carcinoma

Aim: To better predict the survival of cervical squamous cell carcinoma (CESC) patients, we aimed to construct a signature according to different immune infiltration. Methods: We downloaded the RNA sequences of CESC patients from the Cancer Genome Atlas database. By using single-sample gene set enrichment analysis, we separated the samples into high- and low-immunity groups. Then we separated the samples into training and testing datasets and performed the following analyses: univariate, least absolute shrinkage and selection operator analysis, multivariate Cox regression analyses and weighted gene coexpression network analysis using R software. Gene ontology and Kyoto Encyclopedia of Genes and Genomes studies were performed using the Database for Annotation, Visualization and Integrated Discovery website. Results & conclusion: We finally identified a signature with three mRNAs and two lncRNAs: ADGRG5, HSH2D, ZMAT4, RBAKDN and LINC00200. In short, our study constructed an mRNA-lncRNA signature related to immune infiltration to better predict the survival of CESC patients.

Identification of Core Prognosis-Related Candidate Genes in Chinese Gastric Cancer Population Based on Integrated Bioinformatics

Background

Gastric cancer (GC) is one of the leading causes of cancer-related mortality worldwide. There are great geographical differences in the incidence of GC, and somatic mutation rates of driver genes are also different. The present study is aimed at screening core prognosis-related candidate genes in Chinese gastric cancer population based on integrated bioinformatics for the early diagnosis and prognosis of GC.

Methods

In the present study, the differentially expressed genes (DEGs) in GC were identified using four microarray datasets from the Gene Expression Omnibus (GEO) database. The samples of these datasets were all from China. Functional enrichment analysis of DEGs was conducted to evaluate the underlying molecular mechanisms involved in GC. Protein-protein interaction (PPI) network and cytoHubba were performed to determine hub genes associated with GC. Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) were performed to validate the hub genes.

Results

A total of 240 DEGs were obtained through the RRA method, including 80 upregulated genes and 160 downregulated genes. Upregulated genes were mainly enriched in extracellular matrix organization, extracellular matrix, and extracellular matrix structural constituent. The downregulated genes were mainly enriched in digestion, extracellular space, and oxidoreductase activity. The KEGG pathway enrichment analysis showed that the upregulated genes were mainly associated with ECM-receptor interaction, focal adhesion, and PI3K-Akt signaling pathway. And downregulated genes were mainly associated with the metabolism of xenobiotics by cytochrome P450, metabolic pathways, and gastric acid secretion. The transcriptional and translational expression levels of the genes including COL1A1, COL5A2, COL12A1, and VCAN were higher in GC tissues than normal tissues.

Conclusion

A total of four genes including COL1A1, COL5A2, COL12A1, and VCAN were considered potential GC biomarkers in the Chinese population. And ECM-receptor interaction, focal adhesion, and PI3K-Akt signaling pathway were revealed to be important mechanisms of GC. Our findings provide novel insights into the occurrence and progression of GC in the Chinese population.

Translational changes induced by acute sleep deprivation uncovered by TRAP-Seq

Sleep deprivation is a global health problem adversely affecting health as well as causing decrements in learning and performance. Sleep deprivation induces significant changes in gene transcription in many brain regions, with the hippocampus particularly susceptible to acute sleep deprivation. However, less is known about the impacts of sleep deprivation on post-transcriptional gene regulation. To identify the effects of sleep deprivation on the translatome, we took advantage of the RiboTag mouse line to express HA-labeled Rpl22 in CaMKIIα neurons to selectively isolate and sequence mRNA transcripts associated with ribosomes in excitatory neurons. We found 198 differentially expressed genes in the ribosome-associated mRNA subset after sleep deprivation. In comparison with previously published data on gene expression in the hippocampus after sleep deprivation, we found that the subset of genes affected by sleep deprivation was considerably different in the translatome compared with the transcriptome, with only 49 genes regulated similarly. Interestingly, we found 478 genes differentially regulated by sleep deprivation in the transcriptome that were not significantly regulated in the translatome of excitatory neurons. Conversely, there were 149 genes differentially regulated by sleep deprivation in the translatome but not in the whole transcriptome. Pathway analysis revealed differences in the biological functions of genes exclusively regulated in the transcriptome or translatome, with protein deacetylase activity and small GTPase binding regulated in the transcriptome and unfolded protein binding, kinase inhibitor activity, neurotransmitter receptors and circadian rhythms regulated in the translatome. These results indicate that sleep deprivation induces significant changes affecting the pool of actively translated mRNAs.

Identification of Core Genes Involved in the Progression of Cervical Cancer Using an Integrative mRNA Analysis

In spite of being a preventable disease, cervical cancer (CC) remains at high incidence, and it has a significant mortality rate. Although hijacking of the host cellular pathway is fundamental for developing a better understanding of the human papillomavirus (HPV) pathogenesis, a major obstacle is identifying the central molecular targets involved in HPV-driven CC. The aim of this study is to investigate transcriptomic patterns of HPV-infected and normal tissues to identify novel prognostic markers. Analyses of functional enrichment and interaction networks reveal that altered genes are mainly involved in cell cycle, DNA damage, and regulated cell-to-cell signaling. Analysis of The Cancer Genome Atlas (TCGA) data has suggested that patients with unfavorable prognostics are more likely to have DNA repair defects attributed, in most cases, to the presence of HPV. However, further studies are needed to fully unravel the molecular mechanisms of such genes involved in CC.