Mining expression and prognosis of topoisomerase isoforms in non-small-cell lung cancer by using Oncomine and Kaplan-Meier plotter

TOP2A modulates signaling via the AKT/mTOR pathway to promote ovarian cancer cell proliferation

Ovarian cancer (OC) is a form of gynecological malignancy that is associated with worse patient outcomes than any other cancer of the female reproductive tract. Topoisomerase II α (TOP2A) is commonly regarded as an oncogene that is associated with malignant disease progression in a variety of cancers, its mechanistic functions in OC have yet to be firmly established. We explored the role of TOP2A in OC through online databases, clinical samples, in vitro and in vivo experiments. And initial analyses of public databases revealed high OC-related TOP2A expression in patient samples that was related to poorer prognosis. This was confirmed by clinical samples in which TOP2A expression was elevated in OC relative to healthy tissue. Kaplan-Meier analyses further suggested that higher TOP2A expression levels were correlated with worse prognosis in OC patients. In vitro, TOP2A knockdown resulted in the inhibition of OC cell proliferation, with cells entering G1 phase arrest and undergoing consequent apoptotic death. In rescue assays, TOP2A was confirmed to regulate cell proliferation and cell cycle through AKT/mTOR pathway activity. Mouse model experiments further affirmed the key role that TOP2A plays as a driver of OC cell proliferation. These data provide strong evidence supporting TOP2A as an oncogenic mediator and prognostic biomarker related to OC progression and poor outcomes. At the mechanistic level, TOP2A can control tumor cell growth via AKT/mTOR pathway modulation. These preliminary results provide a foundation for future research seeking to explore the utility of TOP2A inhibitor-based combination treatment regimens in platinum-resistant recurrent OC patients.

Multi-modal domain adaptation for revealing spatial functional landscape from spatially resolved transcriptomics

Spatially resolved transcriptomics (SRT) has emerged as a powerful tool for investigating gene expression in spatial contexts, providing insights into the molecular mechanisms underlying organ development and disease pathology. However, the expression sparsity poses a computational challenge to integrate other modalities (e.g. histological images and spatial locations) that are simultaneously captured in SRT datasets for spatial clustering and variation analyses. In this study, to meet such a challenge, we propose multi-modal domain adaption for spatial transcriptomics (stMDA), a novel multi-modal unsupervised domain adaptation method, which integrates gene expression and other modalities to reveal the spatial functional landscape. Specifically, stMDA first learns the modality-specific representations from spatial multi-modal data using multiple neural network architectures and then aligns the spatial distributions across modal representations to integrate these multi-modal representations, thus facilitating the integration of global and spatially local information and improving the consistency of clustering assignments. Our results demonstrate that stMDA outperforms existing methods in identifying spatial domains across diverse platforms and species. Furthermore, stMDA excels in identifying spatially variable genes with high prognostic potential in cancer tissues. In conclusion, stMDA as a new tool of multi-modal data integration provides a powerful and flexible framework for analyzing SRT datasets, thereby advancing our understanding of intricate biological systems.

HERC4 modulates ovarian cancer cell proliferation by regulating SMO-elicited hedgehog signaling

BACKGROUND

HERC4 has been reported to have functions in several types of tumors, but its roles in ovarian cancer have not been studied yet.

METHODS

Primary tissues from ovarian cancer patients and cell lines were collected for real-time PCR. Kaplan-Meier Plotter was used to predict the prognosis of ovarian cancer patients. HERC4 was overexpressed in cells by lentivirus, and CCK-8 assay was performed to evaluate cell viability. Real-time PCR and Western blot were carried out to analyze the mRNA and protein expression, respectively. Xenograft tumor models were established to analyze HERC4 function in vivo.

RESULTS

Firstly, we found that HERC4 was significantly downregulated in ovarian cancer. We then found that ovarian cancer patients with high HERC4 expression had significantly higher overall survival and progression-free survival rates compared with patients with low expression. Then, HERC4 was overexpressed in ovarian cancer cells, and we found that overexpression of HERC4 significantly inhibited ovarian cancer cell growth, as well as the expression of the target protein SMO, and the key proteins in the downstream hedgehog signaling pathway. Finally, the xenograft tumor models revealed that overexpression of HERC4 significantly inhibited tumor growth in vivo.

CONCLUSIONS

Overall, these results indicate that overexpression of HERC4 inhibits cell proliferation of ovarian cancer in vitro and in vivo, suggesting that HERC4 may serve as an effective target for the treatment of ovarian cancer.

Targeting TOP2B as a vulnerability in aging and aging-related diseases

The ongoing trend of rapid aging of the global population has unavoidably resulted in an increase in aging-related diseases. There is an immense amount of interest in the scientific community for the identification of molecular targets that may effectively mitigate the process of aging and aging-related diseases. The enzyme Topoisomerase IIβ (TOP2B) plays a crucial role in resolving the topological challenges that occur during DNA-related processes. It is believed that the disruption of TOP2B function contributes to the aging of cells and tissues, as well as the development of age-related diseases. Consequently, targeting TOP2B appears to be a promising approach for interventions aimed at mitigating the effects of aging. This review focuses on recent advancements in the understanding of the role of TOP2B in the processing of aging and aging-related disorders, thus providing a novel avenue for the development of anti-aging strategies.

Expression and prognosis analysis of TBX2 subfamily in human lung carcinoma

PURPOSE

Lung cancer has a high morbidity and mortality rate of all cancers worldwide. Therefore, there is an urgent need for reliable cancer markers for diagnosis and prognosis of patients with lung cancer.

METHODS

In this study, we used the bioinformatics database to compare the expression of the TBX2 subfamily at the transcriptional and protein levels in non-small cell lung cancer. Then, to confirm our bioinformatics analysis above, we used western bloting to determine the expression of TBX2, TBX3, TBX4 and TBX5 in human lung squamous carcinoma cell lines. Besides, low expression of TBX2 subfamily predicted a poor prognosis of patients with lung cancer. Finally, The methylation database was used to explore the relationship between the low expression of TBX2 subfamily and methylation of gene promoter region.

RESULTS

Our data showed a significant decrease of TBX2 subfamily expression in lung cancer tissues of several histological subtypes. Finally, the methylation of TBX2 subfamily members in the promoter region of NSCLC was significantly higher than that in normal tissues.

CONCLUSION

Our research provided sufficient evidence that TBX2 subfamily might play an inhibitory role in malignancy progression of lung cancer, which is promising to shed light on discovering a novel reliable cancer marker for prognosis of lung cancer patients.

Assessment the value of Pyroptosis-Associated Gasdermin family genes in hepatocellular carcinoma: A Multi-Omics Comprehensive Analysis

Background: Hepatocellular carcinoma (HCC) is one of the common primary cancers of the liver worldwide and leading cause of mortality. Gasdermins (GSDMs) family genes play an important role in the regulation of the normal physiological processes and have been implicated in multiple diseases. However, little is known about the relationship between different GSDMs proteins and HCC. The aim of this study was to explore the potential relationship between the expression, prognosis, genetic variation and immune infiltration of GSDMs family genes and HCC. Methods: We used different bioinformatics common public databases such as GSCA, GEPIA, UALCAN, HPA, Kaplan-Meier Plotter, LinkedOmics, GeneMANIA, STRING, cBioPortal, TIMER and TISIDB to analyze the differential expression of the different GSDMs, prognostic value, genetic alterations, immune cell infiltration and their functional networks in HCC patients. Results: All the members of the GSDMs family exhibited elevated mRNA expression levels in LIHC compared to the normal tissues, while only GSDMB, GSDMD and GSDME showed enhanced protein expression. The mRNA expression of most GSDMs members was found to be elevated in HCC patients at stages I-III (clinical stage) compared to the normal subjects. The expression of GSDMD was correlated with OS and DSS of patients, whereas GSDME was correlated with OS, DSS and RFS of patients. Gene amplification was observed to be main mode of variation in members of the GSDMs family. KEGG pathway analysis showed that genes associated with different members of the GSDMs family were enriched in the pathways of S. aureus infection, intestinal immunity, ribosome and protein assembly, oxidative phosphorylation, osteoclast differentiation and Fc gamma (γ) R-mediated phagocytosis. In addition, expression of both GSDMA and GSDME were found to be correlated most significantly with infiltration of immune cells, while GSDMA and GSDME somatic cell copy number alteration (CAN) were correlated significantly with the infiltration of immune cells. All GSDMs were noted to be associated with distinct subtypes of immune cells, except GSDMC. Conclusions: Our findings have provided useful insights to better understand the roles and functions of GSDMs in HCC that can provide novel direction for developing therapeutic modalities for HCC, including immunotherapy.

NCPAD2 is a favorable predictor of prognostic and immunotherapeutic biomarker for multiple cancer types including lung cancer

BACKGROUND

Non-SMC condensin I complex subunit D2 (NCAPD2) belongs to the chromosomal structural maintenance family. While the different contribution of NCAPD2 to chromosome in mitosis have been thoroughly investigated, much less is known about the expression of NCAPD2 in pan-cancer. Thus, we used a bioinformatics dataset to conduct a pan-cancer analysis of NCAPD2 to determine its regulatory role in tumors.

METHODS

Multiple online databases were analyzed NCAPD2 gene expression, protein level, patient survival and functional enrichment in pan-cancer. Genetic alteration and tumor stemness of NCAPD2 were analyzed using cBioPortal and SangerBox. The GSCA and CellMiner were used to explore the relationship between NCAPD2 and drug sensitivity. The diagnostic value of prognosis was evaluated by ROC curve. Subsequently, the immune infiltration level and immune subtype of NCAPD2 in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) were analyzed using TIMER1 and TISIDB.

RESULTS

NCAPD2 gene expression was significantly higher in most cancers and associated with clinical stage and poor prognosis. Genomic heterogeneity of NCAPD2 promoted the occurrence and development of tumors. GO enrichment analysis suggested NCAPD2 might be involved in DNA repair and immune response. NCAPD2 was involved in immune infiltration of LUAD and LUSC. ROC curves showed that NCAPD2 has important prognosis diagnostic value in LUAD and LUSC. Moreover, NCAPD2 was drug sensitive to topotecan, which may be an optimize immunotherapy.

CONCLUSIONS

It was found that NCAPD2 was overexpressed in pan-cancers, which was associated with poor outcomes. Importantly, NCAPD2 could be a diagnostic marker and an immune related biomarker for LUAD and LUSC.

KRAS modulates immune infiltration levels and survival outcomes in patients with lung adenocarcinoma

The murine sarcoma virus oncogene (KRAS) is a key gene associated with tumorigenesis and chemotherapy resistance. However, little is known about the molecular mechanisms and immune infiltration of RASs in lung adenocarcinoma. Gene Expression Profiling Interaction Analysis was used for RASs expression analysis, and Kaplan-Meier analysis was used to analyze the potential of RASs in clinical prognosis. The effect of KRAS on immune infiltration was analyzed by TIMER. In addition, the correlation between KRAS expression and molecular mechanisms was investigated by TIMER and Cancer Single-cell State Atlas (Cancer SEA). KRAS expression levels were associated with good prognosis and tumor progression. Furthermore, KRAS expression correlates with several immune cell markers and regulates tumorigenesis. KRAS expression is involved in the regulation of multiple oncogenes and tumorigenesis, especially in the prognosis and immune infiltration of lung adenocarcinoma.

SERPINE1 and SERPINB7 as potential biomarkers for intravenous vitamin C treatment in non-small-cell lung cancer

High dose intravenous vitamin C (IVC) has been proposed as a pro-oxidant anticancer agent. However, there is a lack of biomarkers that are specific for this treatment. Here, we explored profiles of gene expression responding to IVC treatment in non-small cell lung cancer (NSCLC) cells as an effort for potential biomarker discovery. Genome-wide RNA-seq was performed in human NSCLC cell lines treated with pharmacological concentrations of vitamin C(VitC) for differential expression of genes. The identified genes were analyzed for correlations with patient prognosis using data from the Kaplan-Meier Plotter and the Human Protein Atlas databases. Further, tumor samples from a retrospective study of 153 NSCLC patients were analyzed with immunohistochemistry for expression of targeted genes, and patient prognosis was correlated to these genes. Two genes, namely SERPINE1 and SERPINB7 were found to be downregulated in NSCLC cells following VitC treatment. Combined patient data from the cohort analysis and online databases revealed that these 2 genes presented an unfavorable prognostic prediction of overall survival (OS) in NSCLC patients receiving standard of care. However, high expression level of these 2 genes were associated with prolonged OS in NSCLC patients receiving IVC in addition to standard of care. These data revealed that SERPINE1 and SERPINB7 have the potential to serve as predictive factors indicating favorable responses to IVC treatment in patients with NSCLC. Further validations are warranted.

Integration of bioinformatics and machine learning strategies identifies APM-related gene signatures to predict clinical outcomes and therapeutic responses for breast cancer patients

BACKGROUND

Tumor antigenicity and efficiency of antigen presentation jointly influence tumor immunogenicity, which largely determines the effectiveness of immune checkpoint blockade (ICB). However, the role of altered antigen processing and presentation machinery (APM) in breast cancer (BRCA) has not been fully elucidated.

METHODS

A series of bioinformatic analyses and machine learning strategies were performed to construct APM-related gene signatures to guide personalized treatment for BRCA patients. A single-sample gene set enrichment analysis (ssGSEA) algorithm and weighted gene co-expression network analysis (WGCNA) were combined to screen for BRCA-specific APM-related genes. The non-negative matrix factorization (NMF) algorithm was used to divide the cohort into different clusters and the fgsea algorithm was applied to investigate the altered signaling pathways. Random survival forest (RSF) and the least absolute shrinkage and selection operator (Lasso) Cox regression analysis were combined to construct an APM-related risk score (APMrs) signature to predict overall survival. Furthermore, a nomogram and decision tree were generated to improve predictive accuracy and risk stratification for individual patients. Based on Tumor Immune Dysfunction and Exclusion (TIDE) method, random forest (RF) and Lasso logistic regression model were combined to establish an APM-related immunotherapeutic response score (APMis). Finally, immune infiltration, immunomodulators, mutational patterns, and potentially applicable drugs were comprehensively analyzed in different APM-related risk groups. IHC staining was used to assess the expression of APM-related genes in clinical samples.

RESULTS

In this study, APMrs and APMis showed favorable performances in risk stratification and therapeutic prediction for BRCA patients. APMrs exhibited more powerful prognostic capacity and accurate survival prediction compared to conventional clinicopathological features. APMrs was closely associated with distinct mutational patterns, immune cell infiltration and immunomodulators expression. Furthermore, the two APM-related gene signatures were independently validated in external cohorts with prognosis or immunotherapeutic responses. Potential applicable drugs and targets were mined in the APMrs-high group. APM-related genes were further validated in our in-house samples.

CONCLUSION

The APM-related gene signatures established in our study could improve the personalized assessment of survival risk and guide ICB decision-making for BRCA patients.

Clinical importance and PI3K/Akt pathway-dependent anti-proliferative role of PALMD and DPT in breast cancer

This study aimed to identify novel differentially expressed genes in breast cancer and to explore the clinical value and the anti-tumor or oncogenic effects of the identified genes using bioinformatics analysis and in vitro experiments. The differentially expressed genes in breast cancer patients were identified using Gene Expression Omnibus (GEO) database with the cut-off criteria p < 0.05 and |logFC| > 1. The expression levels of palmdelphin (PALMD) and dermatopontin (DPT) in normal tissues and breast cancer tissues were evaluated based on GEPIA and UALCAN databases. PALMD and DPT expression levels in clinical subgroups of patients with breast cancer were analyzed to assess the association of PALMD and DPT expression with clinical characteristics. The prognostic and diagnostic values of PALMD and DPT in breast cancer were evaluated from Kaplan-Meier (K-M) survival curves and receiver operating characteristic (ROC) curves. Pearson's correlation coefficient was performed using LinkedOmics. KEGG pathway enrichment analysis was performed using DAVID. The protein levels were evaluated using western blot analysis. Cell proliferation was assessed using MTT and EdU assays. Two important genes, PALMD and DPT, were identified in breast cancer. The expression levels of PALMD and DPT were significantly lower in breast cancer tissues. The expression levels of PALMD were closely related to age, histological type, and T stage of breast cancer patients. The expression levels of DPT were closely related to age, histological type, T stage, N stage, estrogen receptor status, and progesterone receptor status of breast cancer patients. The K-M survival curves showed that PALMD or DPT was not an independent prognostic factor for breast cancer. The ROC curves showed that both PALMD and DPT had good diagnostic potential for breast cancer. KEGG pathway enrichment results showed that PI3K/Akt pathway was an important overlapping signaling for PALMD and DPT. Further studies proved that overexpression of PALMD and DPT inhibited proliferation in MCF-7 and MDA-MB-231 cells by suppressing the PI3K/Akt pathway. PALMD and DPT knockdown promoted proliferation in MCF-7 and MDA-MB-231 cells by activating the PI3K/Akt pathway. These results collectively suggested that PALMD and DPT might serve as potential diagnostic biomarkers and therapeutic targets for breast cancer.

The potential bioactive ingredients and hub genes of five TCM prescriptions against lung adenocarcinoma were explored based on bioinformatics

Analysis of the commonness of several prescriptions of traditional Chinese medicine (TCM) in the treatment of lung adenocarcinoma (LUAD) based on bioinformatics. Searched the TCM prescriptions for the treatment of LUAD in the literature published in the database, searched ingredients in the TCM through TCMSP and Swiss target prediction databases (OB ≥ 30%, DL > 0.18, Caco-2 > 0), and predicted the potential targets. GEO database retrieved LUAD gene chip data and screened (P < 0.05, | log2 (fold change) |> 1). The biological function, hub gene selection and survival period, immune infiltration, methylation, copy number variations (CNVs), and single-nucleotide variants (SNV) of hub genes were analyzed by DAVID, STRING, Kaplan-Meier plotter database, Cytoscape software, GSCALite database, and TIMER2.0. In this study, 5 TCM prescriptions were analyzed, and a total of 173 ingredients were obtained through database search, including 35 coincidence ingredients, a total of 603 potential targets, 621 LUAD-related genes, 16 up-regulated genes, and 31 down-regulated genes. A total of 61 terms of biological process (BP), 14 terms of cellular component (CC), and 14 terms of molecular function (MF) were obtained. Twenty core genes were obtained, including 15 genes with different survival periods, which were closely related to immune cells (B cell, CD8 + T cell, CD4 + T cell, macrophage, neutrophil, and dendritic cells). The low expression of ADRB2 and MAOA and the high expression of AUARK, CDK1, KIF11, MIF, TOP2A, and TTK were associated with the survival rate of LUAD patients (P < 0.05). Baicalein, Arachidonate, Hederagenin, and hub genes may become potential drugs and potential targets for LUAD treatment. Evaluated the efficacy of TCM in the treatment of LUAD from macro to micro, mined the hub genes, and predicted the mechanism of action, so as to lay the foundation for the development of new drugs of TCM, prescription optimization, or disease control.

Prognostic value and immunological role of PTPN21 in pan-cancer analysis

Introduction

At present, cancer remains a persistent public health challenge facing the whole world. Studies have found that PTPN21 is associated with the development of cancer. However, the prognostic potential of PTPN21 in pan-cancer remains unclear. In this work, we aimed to analyze the expression and prognostic value of PTPN21 in pan-cancer and to further study the relationship between PTPN21 and immune infiltration.

Material and methods

TCGA and GEO data were used for expression and survival analysis. Genetic alterations in PTPN21 from TCGA cancer were studied in cBioPortal. TIMER2 was used to evaluate the correlation between PTPN21 expression and immune infiltration. The R packages "ggplot2" and "clusterProfiler" were used for GO and KEGG analysis.

Results

PTPN21 was found to be a valuable diagnostic biomarker in multiple cancers, including bladder urothelial carcinoma (BLCA), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), and lung squamous cell carcinoma (LUSC). In addition, we observed that PTPN21 expression was associated with a variety of tumor mutations. Our results indicated a correlation between PTPN21 expression and immune infiltration. Enrichment analysis showed that PTPN21 was mainly involved in the regulation of neuroactive ligand-receptor interaction.

Conclusions

Our study showed that PTPN21 expression is associated with clinical prognosis, mutation, and immune infiltration of tumors. PTPN21 may be a potential biomarker for many cancers, especially in KIRC.

Pan-Cancer Analysis Reveals PPRC1 as a Novel Prognostic Biomarker in Ovarian Cancer and Hepatocellular Carcinoma

Background and Objectives: As is well understood, peroxisome proliferator-activated receptor gamma cofactor-related 1 (PPRC1) plays a central role in the transcriptional control of the mitochondrial biogenesis and oxidative phosphorylation (OXPHOS) process, yet its critical role in pan-cancer remains unclear. Materials and Methods: In this paper, the expression levels of PPRC1 in different tumor tissues and corresponding adjacent normal tissues were analyzed based on four databases: The Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE), The Cancer Genome Atlas (TCGA), and Tumor Immune Estimation Resource (TIMER). Meanwhile, the prognostic value of PPRC1 was inferred using Kaplan-Meier plotter and forest-plot studies. In addition, the correlation between PPRC1 expression and tumor immune cell infiltration, immune checkpoints, and the tumor-stemness index was analyzed using TCGA and TIMER databases. Results: According to our findings, the expression level of PPRC1 was found to be different in different cancer types and there was a positive correlation between PPRC1 expression and prognosis in several tumor types. In addition, PPRC1 expression was found to be significantly correlated with immune cell infiltration, immune checkpoints, and the tumor-stemness index in both ovarian and hepatocellular carcinoma. Conclusions: PPRC1 demonstrated promising potential as a novel biomarker in pan-cancer due to its potential association with immune cell infiltration, expression of immune checkpoints, and the tumor-stemness index.

Virtual screening and multilevel precision-based prioritisation of natural inhibitors targeting the ATPase domain of human DNA topoisomerase II alpha

Human DNA topoisomerase II alpha (hTopIIα) is a classic chemotherapeutic drug target. The existing hTopIIα poisons cause numerous side effects such as the development of cardiotoxicity, secondary malignancies, and multidrug resistance. The use of catalytic inhibitors targeting the ATP-binding cavity of the enzyme is considered a safer alternative due to the less deleterious mechanism of action. Hence, in this study, we carried out high throughput structure-based virtual screening of the NPASS natural product database against the ATPase domain of hTopIIα and identified the five best ligand hits. This was followed by comprehensive validation through molecular dynamics simulations, binding free energy calculation and ADMET analysis. On stringent multilevel prioritization, we identified promising natural product catalytic inhibitors that showed high binding affinity and stability within the ligand-binding cavity and may serve as ideal hits for anticancer drug development.Communicated by Ramaswamy H. Sarma.

GLUT10 is a novel immune regulator involved in lung cancer immune cell infiltration and predicts worse survival when transcriptionally downregulated

Background

Glucose transporter 10 (GLUT10) is encoded by the SLC2A10 gene. Our recent investigations have shown that GLUT10 is not only involved in glucose metabolism but also involved in the body's immune response to cancer cells. However, the role of GLUT10 in tumor prognosis and in tumor immunity has not been reported.

Methods

We knocked down SLC2A10 and performed transcriptome sequencing to analyse the biological function of GLUT10 and found that GLUT10 may be involved in immune signaling. Then, we studied the expression level of SLC2A10 in cancers by the Oncomine database and Tumor Immune Estimation Resource (TIMER) site. We also evaluated the prognostic potential of SLC2A10 in different cancers using the Kaplan‒Meier plotter database and PrognoScan online software. The correlations between SLC2A10 expression and immune infiltrates were analysed by TIMER. In addition, correlations between SLC2A10 expression and gene marker sets of immune infiltrates were analysed by TIMER and Gene Expression Profiling Interactive Analysis (GEPIA). Immunofluorescence staining of cyclooxygenase-2 (COX-2) and GLUT10 in lung cancer tissue and adjacent tissue was performed to confirm our findings from the database research.

Results

Knocking down SLC2A10 widely activated immune and inflammatory signaling. SLC2A10 was abnormally expressed in several tumors. The expression level of SLC2A10 was closely correlated with cancer prognosis. Low SLC2A10 expression was related to poorer prognosis and increased malignancy of lung cancer. Lung cancer patients with low expression of SLC2A10 have a much shorter median survival time than patients with high expression of SLC2A10. SLC2A10 expression is closely related to the infiltration of different types of immune cells, particularly macrophages. Both database research and lung cancer sample research revealed that GLUT10 might modulate immune cell infiltration via the COX-2 pathway.

Conclusions

By transcriptome experiments, database studies, and human sample studies, we found that GLUT10 is a new immune signaling molecule involved in tumor immunity, especially in the immune cell infiltration of lung adenocarcinoma (LUAD). GLUT10 may modulate the immune cell infiltration of LUAD via the COX-2 pathway.

Upregulation of MAD2L1 mediated by ncRNA axis is associated with poor prognosis and tumor immune infiltration in hepatocellular carcinoma: A review

BACKGROUND

The mortality rate and prognosis of patients with hepatocellular carcinoma (HCC) are well known. A variety of highly malignant human cancers express mitotic arrest deficient 2 like 1 (MAD2L1), a transcription factor that plays a critical role in their development and progression. However, MAD2L1's particular mechanisms and effects on HCC remain uncertain.

METHODS

We performed a pan-cancer analysis for MAD2L1 prognosis and expression using The Cancer Genome Atlas and Genotype-Tissue Expression data in the present study. MAD2L1 may act as an oncogene in HCC, and a combination of in silico analyses, including expression, survival, and correlation analyses, were performed to identify non-coding ribonucleic acids (ncRNAs) that contribute to MAD2L1 overexpression.

RESULTS

In conclusion, MAD2L1 is most likely regulated by HCP5/miRNA-139-5p/MAD2L1 in HCC based on its upstream ncRNA-related pathway. A significant positive association was also found between MAD2L1 levels and tumor immune cell infiltration, immune cell biomarkers, and immune checkpoint expression.

CONCLUSION

Our findings demonstrate that ncRNA-mediated upregulation of MAD2L1 in HCC is closely related to poor prognosis and tumor infiltration.

ARNTL2 is an indicator of poor prognosis, promotes epithelial-to-mesenchymal transition and inhibits ferroptosis in lung adenocarcinoma

OBJECTIVES

ARNTL2, as a circadian transcription factor, has been recently proposed to play an important role in a variety of tumors. however, the role of ARNTL2 in lung carcinogenesis and progression remains unclear. The purpose of this study was to investigate the effect of ARNTL2 on the clinical characteristics and prognosis of lung adenocarcinoma and to explore the relationship between ARNTL2 and EMT, ferroptosis in lung adenocarcinoma.

METHODS

The Cancer Genome Atlas (TCGA) database's multi-omics data were downloaded using the Xena browser. Based on the expression levels of ARNTL2, patients with lung adenocarcinoma from TCGA were divided into two groups: those with high ARNTL2 expression and those with low ARNTL2 expression. ARNTL2 was studied for its effects on lung adenocarcinoma's clinicopathological, genomic, and immunological characteristics. Furthermore, in vivo and in vitro assays were used to confirm the impact of ARNLT2 knockdown on lung adenocarcinoma cells.

RESULTS

We found ARNTL2 is highly expressed in lung adenocarcinoma and was an independent predictor of a poor prognosis in patients with lung adenocarcinoma. In addition, we demonstrated that knockdown of ARNTL2 promoted ferroptosis, inhibited EMT, cell proliferation, migration and invasion in lung adenocarcinoma. In contrast, overexpressing ARNTL2 yielded the opposite results.

CONCLUSIONS

ARNTL2 is an independent unfavorable prognostic factor for lung adenocarcinoma. It plays a facilitating role in the development of lung adenocarcinoma, especially in promoting EMT and inhibiting ferroptosis, revealing that ARNTL2 may be a potential biomarker for lung adenocarcinoma.

Circulating serum miR-1246 and miR-1229 as diagnostic biomarkers in colorectal carcinoma

Background

Colorectal cancer (CRC) is one of the most common cancers worldwide. Although colonoscopy is considered as the "Gold Standard" technique to detect CRC, its application is invasive and cost incurred. Thus, noninvasive or minimally invasive approaches are of utmost importance. The aberrant expression of some microRNAs (miRNAs, miRs) has been suggested in association with CRC pathogenesis. This study aimed to validate if circulating serum miR-1229 and miR-1246 are diagnostic biomarkers for CRC.

Materials and Methods

Serum samples were isolated from 45 CRC patients and also 45 healthy controls (HC). The expression levels of circulating serum-derived miR-1229 and miR-1246 were evaluated by quantitative real-time polymerase chain reaction. Receiver operating characteristic (ROC) curves were constructed to evaluate the CRC diagnostic accuracy of selected miRNAs. Furthermore, the association of candidate miRNAs and clinicopathological characteristics were evaluated. Functional enrichment of the candidate miRNAs was applied using in silico tools.

Results

The expression of miR-1229 and miR-1246 was significantly higher in CRC patients than HC (P < 0.0001) and also was found in association with lymph node metastasis (P < 0.05). We demonstrated a significant up-regulation of serum-derived miR-1246 in advanced tumor-node-metastasis stage III of CRC patients (P < 0.05). Areas under the ROC curve of miR-1229 and miR-1246 were 0.81 and 0.84, respectively (P < 0.0001).

Conclusion

We confirmed the capability of circulating serum miR-1229 and miR-1246 as novel diagnostic biomarkers for CRC.

Network module function enrichment analysis of lung squamous cell carcinoma and lung adenocarcinoma

BACKGROUND

Lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) are the two major subtypes of non-small cell lung cancer that pose a serious threat to human health. However, both subtypes currently lack effective indicators for early diagnosis.

METHODS

To identify tumor-specific indicators and predict cancer-related signaling pathways, LUSC and LUAD gene weighted co-expression networks were constructed. Combined with clinical data, core genes in LUSC and LUAD modules were then screened using protein-protein interaction networks and their functions and pathways were analyzed. Finally, the effect of core genes on survival of LUSC and LUAD patients was evaluated.

RESULTS

We identified 12 network modules in LUSC and LUAD, respectively. LUSC modules "purple" and "green" and LUAD modules "brown" and "pink" are significantly associated with overall survival and clinical traits of tumor node metastasis, respectively. Eleven genes from LUSC and eight genes from LUAD were identified as candidate core genes, respectively. Survival analysis showed that high expression of SLIT3, ABI3BP, MYOCD, PGM5, TNXB, and DNAH9 are associated with decreased survival in LUSC patients. Furthermore, high expression of BUB1, BUB1B, TTK, and UBE2C are associated with lower patient survival.

CONCLUSIONS

We found biomarker genes and biological pathways for LUSC and LUAD. These network hub genes are associated with clinical characteristics and patient outcomes and they may play important roles in LUSC and LUAD.

Shared network pattern of lung squamous carcinoma and adenocarcinoma illuminates therapeutic targets for non-small cell lung cancer

Background

Non-small cell lung cancer (NSCLC) is a malignant tumor with high mortality. Lung squamous carcinoma (LUSC) and lung adenocarcinoma (LUAD) are the common subtypes of NSCLC. However, how LUSC and LUAD are compatible remains to be elucidated.

Methods

We used a network approach to find highly interconnected genes shared with LUSC and LUAD, and we then built modules to assess the degree of preservation between them. To quantify this result, Z-scores were used to summarize the interrelationships between LUSC and LUAD. Furthermore, we correlated network hub genes with patient survival time to identify risk factors.

Results

Our findings provided a look at the regulatory pattern for LUSC and LUAD. For LUSC, several genes, such as AKR1C1, AKR1C2, and AKR1C3, play key roles in regulating network modules of cell growth pathways. In addition, CCL19, CCR7, CCL21, and LY9 are enriched in LUAD network modules of T lymphocyte-related pathways. LUSC and LUAD have similar expressed gene expression patterns. Their networks share 46 hub genes with connectivity greater than 0.9. These genes are correlated with patient survival time. Among them, the expression level of COL5A2 in LUSC and LUAD is higher than that in normal tissues, which is closely related to the poor prognosis of LUSC and LUAD patients.

Conclusion

LUSC and LUAD share a network pattern. COL5A2 may be a risk factor in poor prognosis in LUSC and LUAD. The common landscape of LUSC and LUAD will help better define the regulation of NSCLC candidate genes and achieve the goals of precision medicine.

Bioinformatics and Patient Survival Analysis of Digestive Tract Tumor Marker NCAPG Based on Public Medical Databases

The digestive tract tumor disease is a serious threat to human health. The effective identification of digestive tract tumor markers with specific characteristics is the key to the diagnosis, treatment, recognition, and rehabilitation analysis of digestive tract tumor diseases. Public medical data resource platforms represented by Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), and Human Protein Atlas (HPA) databases provide a new path for knowledge management and knowledge discovery in the medical field. Therefore, a computational analysis framework for tumor marker recognition was established to mine from massive and diversified data sets and explore the diagnosis, expression, and prognosis of Non-SMC Condensin I Complex, Subunit G (NCAPG) in gastrointestinal tumors. Patient survival and correlation analyses suggested the mRNA and protein levels of NCAPG were highly expressed in different digestive tract tumors. This study provides new treatment methods for patients with gastrointestinal cancer and a reference for the public.

Comprehensive analysis identifies as a critical prognostic prediction gene in breast cancer

BACKGROUND

Aurora kinases (AURKs) family plays a vital role not only in cell division but also in tumorigenesis. However, there are still rare systematic analyses of the diverse expression patterns and prognostic value of the AURKs family in breast cancer (BC). Systematic bioinformatics analysis was conducted to explore the biological role, prognostic value, and immunologic function of AURKs family in BC.

METHODS

The expression, prognostic value, and clinical functions of AURKs family in BC were evaluated with several bioinformatics web portals: ONCOMINE Gene Expression Profiling Interactive Analysis, Kaplan-Meier plotter, cBioPortal, Metascape, GeneMANIA, and LinkedOmics; and the result was verified using human tissues.

RESULTS

The expression of AURKA and AURKB were upregulated in BC in subgroup analyses based on tumor stage (all P   <  0.05). BC patients with high AURKA and AURKB expression had a worse overall survival, relapse-free survival, and distant metastasis-free survival (all P   <  0.05). Verification experiment revealed that AURKA and AURKB were upregulated in BC ( P  < 0.05). AURKA and AURKB were specifically associated with several tumor-associated kinases (polo-like kinase 1 and cyclin-dependent kinase 1), miRNAs (miR-507 and miR-381), and E2F transcription factor 1. Moreover, AURKA and AURKB were correlated with immune cell infiltration. Functional enrichment analysis revealed that AURKA and AURKB were involved in the cell cycle signaling pathway, platinum drug resistance signaling pathway, ErbB signaling pathway, Hippo signaling pathway, and nucleotide-binding and oligomerization domain-like receptor signaling pathway.

CONCLUSIONS

Aurora kinases AURKA and AURKB could be employed as novel prognostic biomarkers or promising therapeutic targets for BC.

An integrative pan cancer analysis of RET aberrations and their potential clinical implications

RET (rearranged during transfection), encoding a tyrosine kinase receptor, is a novel therapeutic target for cancers. The aberrations of RET are commonly found in cancers. Here, we profiled a comprehensive genomic landscape of RET mutations, copy number variants (CNVs), co-occurrence of RET and its mRNA expression and methylation levels in pan cancer, paving the way to the development of new RET-targeted therapies in clinic. Analysis of RET somatic mutations, CNVs, co-occurrence, mRNA expression and methylation were performed among 32 cancer types from The Cancer Genome Atlas (TCGA) dataset covering a total of 10,953 patients with 10,967 samples. RET aberrations were found in 3.0% of diverse cancers. The top two RET-altered tumors were skin cutaneous melanoma (SKCM) and uterine corpus endometrial carcinoma (UCEC) with dominant mutations in the other and PKinase_Tyr domains. RET-G823E and RET-S891L were most commonly found in SKCM and UCEC. Thyroid carcinoma (THCA) demonstrated the highest rate of coiled-coil domain containing 6 (CCDC6)-RET fusions, which constitutively activate RET kinase. Two FDA-approved RET inhibitors—pralsetinib and selpercatinib have been implied for the treatment of patients with RET S891L mutant UCEC and the treatment of patients with metastatic RET-fusion positive THCA and non-small cell lung cancer (NSCLC) at therapeutic level 1. We also identified four RET M918T-altered cases in patients with pheochromocytoma and paraganglioma (PCPG), which may induce drug resistance against multikinase inhibitors. Next, 273 co-occurring aberrations, most frequently in Notch signaling, TGF-β pathway, cell cycle, and Ras-Raf-MEK-Erk/JNK signaling, were uncovered among 311 RET altered cases. TP53 mutations (162 patients) leads to the most significant co-occurrence associated with RET aberrations. Furthermore, the RET expression was found most significantly increased in breast invasive carcinoma (BRCA) and neck squamous cell carcinoma (HNSC), as compared to their corresponding normal tissues. At last, patients with higher expression and sequence variant frequency have a worse prognosis, such as sarcoma patients. This work provided a profound and comprehensive analysis of RET and co-occurred alterations, RET mRNA expression and the clinical significance in pan cancer, offering new insights into targeted therapy for patients with RET anomalies.

A comprehensive pan-cancer analysis of the expression characteristics, prognostic value, and immune characteristics of TOP1MT

Background: Mitochondria are at the heart of a number of metabolic pathways providing enormous energy for normal cell growth and regulating tumor cell growth as well as survival. Mitochondrial topoisomerase I (TOP1MT) is a type IB topoisomerase found in the mitochondria of vertebrates. However, no pan-cancer analysis of TOP1MT has been reported. This study aims to explore TOP1MT expression in pan-cancer tissues and identify whether it can be a target for mitochondrial anticancer therapy.

Methods and results: The original TOP1MT expression data in 33 different types of cancer patients were downloaded from the TCGA and GTEx databases. TOP1MT was highly expressed in cancer tissues, including BLCA, BRCA, CHOL, COAD, DLBC, ESCA, GBM, HNSC, KIRC, KIRP, LGG, LIHC, LUAD, LUSC, PAAD, PCPG, PRAD, READ, SKCM, STAD, THYM, UCEC, and UCS. According to Kaplan-Meier survival curve analysis, high TOP1MT expression in BLCA, HNSC, KIRP, PAAD, UCEC, and LIHC cancer tissues was linked to poor prognosis of cancer patients, i.e., poor OS, disease-specific survival, and PFI. Linkedomics analysis identified a positive correlation of TOP1MT expression with CNA, but a negative correlation with methylation. TOP1MT expression significantly correlated with immune cells and immune checkpoints in the TIMER database. Functional analysis showed a close relationship between TOP1MT expression and ribosomes.

Conclusion: In summary, TOP1MT is a potential biomarker for mitochondrial anticancer therapy and cancer immunotherapy.

Comprehensive analyses of PDHA1 that serves as a predictive biomarker for immunotherapy response in cancer

Recent studies have proposed that pyruvate dehydrogenase E1 component subunit alpha (PDHA1), a cuproptosis-key gene, is crucial to the glucose metabolism reprogram of tumor cells. However, the functional roles and regulated mechanisms of PDHA1 in multiple cancers are largely unknown. The Cancer Genome Atlas (TCGA), GEPIA2, and cBioPortal databases were utilized to elucidate the function of PDHA1 in 33 tumor types. We found that PDHA1 was aberrantly expressed in most cancer types. Lung adenocarcinoma (LUAD) patients with high PDHA1 levels were significantly correlated with poor prognosis of overall survival (OS) and first progression (FP). Kidney renal clear cell carcinoma (KIRC) patients with low PDHA1 levels displayed poor OS and disease-free survival (DFS). However, for stomach adenocarcinoma (STAD), the downregulated PDHA1 expression predicted a good prognosis in patients. Moreover, we evaluated the mutation diversity of PDHA1 in cancers and their association with prognosis. We also analyzed the protein phosphorylation and DNA methylation of PDHA1 in various tumors. The PDHA1 expression was negatively correlated with tumor-infiltrating immune cells, such as myeloid dendritic cells (DCs), B cells, and T cells in pan-cancers. Mechanically, we used single-cell sequencing to discover that the PDHA1 expression had a close link with several cancer-associated signaling pathways, such as DNA damage, cell invasion, and angiogenesis. At last, we conducted a co-expressed enrichment analysis and showed that aberrantly expressed PDHA1 participated in the regulation of mitochondrial signaling pathways, including oxidative phosphorylation, cellular respiration, and electron transfer activity. In summary, PDHA1 could be a prognostic and immune-associated biomarker in multiple cancers.

A Pan-Cancer Analysis Reveals CLEC5A as a Biomarker for Cancer Immunity and Prognosis

Background

CLEC5A is a member of the C-type lectin superfamily. It can activate macrophages and lead to a series of immune-inflammation reactions. Previous studies reveal the role of CLEC5A in infection and inflammation diseases.

Method

We acquire and analyze data from The Cancer Genome Atlas (TCGA) database, Genotype-Tissue Expression (GTEx) database, and other comprehensive databases via GSCALite, cBioPortal, and TIMER 2.0 platforms or software. Single-cell sequencing analysis was performed for quantifying the tumor microenvironment of several types of cancers.

Results

CLEC5A is differentially expressed in a few cancer types, of which overexpression accompanies low overall survival of patients. DNA methylation mainly negatively correlates with CLEC5A expression. Moreover, CLEC5A is positively related to immune infiltration, including macrophages, cancer-associated fibroblasts (CAFs), and regulatory T cells (Tregs). Immune checkpoint genes are significantly associated with CLEC5A expression in diverse cancers. In addition, CLEC5A expression correlates with mismatch repair (MMR) in several cancers. Tumor mutation burden (TMB), microsatellite instability (MSI), and neoantigens show a positive association with CLEC5A expression in several cancers. Furthermore, CLEC5A in cancer correlates with signal transduction, the immune system, EMT, and apoptosis process. The drug sensitivity analysis screens out potential therapeutic agents associated with CLEC5A expression, including FR-180204, Tivozanib, OSI-930, Linifanib, AC220, VNLG/124, Bexarotene, omacetaxine mepesuccinate, narciclasine, leptomycin B, PHA-793887, LRRK2-IN-1, and CR-1-31B.

Conclusion

CLEC5A overexpresses in multiple cancers in contrast to normal tissues, and high CLEC5A expression predicts poor prognosis of patients and immune infiltration. CLEC5A is a potential prognostic biomarker of diverse cancers and a target for anti-tumor therapy.

Combined analysis of expression, prognosis and immune infiltration of GINS family genes in human sarcoma

Objective: This study was undertaken to explore the expression and prognostic value of GINS family in human sarcoma, as well as the association between the expression levels of the GINS family and sarcoma immune infiltration.

Results: We discovered that the mRNA expression levels of GINS1, GINS2, GINS3, and GINS4 were all higher in the majority of tumor tissues than in normal samples, of course, including sarcoma. Through the CCLE, all the four members expression were observed in high levels in sarcoma cell lines. In Gene Expression Profiling Analysis (GEPIA) and Kaplan-Meier Plotter, our results indicated that the poor overall survival (OS), disease-free survival (DFS) and relapse free survival (RFS) were tightly associated with the increased expression of GINS genes. In TIMER database, we found that highly expressed GINS was significantly correlated with the low infiltration level of CD4+ T cell and macrophage.

Conclusions: The four GINS family members were all the prognostic biomarkers for the prognosis of human sarcoma and can reduce the level of immune cell infiltration in the sarcoma microenvironment.

Methods: In terms of the expression levels of mRNA for GINS family members, a particular contrast in various cancers, especially human sarcoma, was conducted through ONCOMINE and GEPIA and CCLE databases. Kaplan-Meier Plotter was used to identify the prognostic value of GINS family in sarcoma. The relationship between the expression level of GINS and the infiltration of immune cells was analyzed in TIMER database.

Identifying General Tumor and Specific Lung Cancer Biomarkers by Transcriptomic Analysis

The bioinformatic pipeline previously developed in our research laboratory is used to identify potential general and specific deregulated tumor genes and transcription factors related to the establishment and progression of tumoral diseases, now comparing lung cancer with other two types of cancer. Twenty microarray datasets were selected and analyzed separately to identify hub differentiated expressed genes and compared to identify all the deregulated genes and transcription factors in common between the three types of cancer and those unique to lung cancer. The winning DEGs analysis allowed to identify an important number of TFs deregulated in the majority of microarray datasets, which can become key biomarkers of general tumors and specific to lung cancer. A coexpression network was constructed for every dataset with all deregulated genes associated with lung cancer, according to DAVID’s tool enrichment analysis, and transcription factors capable of regulating them, according to oPOSSUM´s tool. Several genes and transcription factors are coexpressed in the networks, suggesting that they could be related to the establishment or progression of the tumoral pathology in any tissue and specifically in the lung. The comparison of the coexpression networks of lung cancer and other types of cancer allowed the identification of common connectivity patterns with deregulated genes and transcription factors correlated to important tumoral processes and signaling pathways that have not been studied yet to experimentally validate their role in lung cancer. The Kaplan–Meier estimator determined the association of thirteen deregulated top winning transcription factors with the survival of lung cancer patients. The coregulatory analysis identified two top winning transcription factors networks related to the regulatory control of gene expression in lung and breast cancer. Our transcriptomic analysis suggests that cancer has an important coregulatory network of transcription factors related to the acquisition of the hallmarks of cancer. Moreover, lung cancer has a group of genes and transcription factors unique to pulmonary tissue that are coexpressed during tumorigenesis and must be studied experimentally to fully understand their role in the pathogenesis within its very complex transcriptomic scenario. Therefore, the downstream bioinformatic analysis developed was able to identify a coregulatory metafirm of cancer in general and specific to lung cancer taking into account the great heterogeneity of the tumoral process at cellular and population levels.

Identification and Validation of lncRNA-SNHG17 in Lung Adenocarcinoma: A Novel Prognostic and Diagnostic Indicator

Background

Lung cancer has the highest death rate among cancers globally. Accumulating evidence has indicated that cancer-related inflammation plays an important role in the initiation and progression of lung cancer. However, the prognosis, immunological role, and associated regulation axis of inflammatory response-related gene (IRRGs) in non-small-cell lung cancer (NSCLC) remains unclear.

Methods

In this study, we perform comprehensive bioinformatics analysis and constructed a prognostic inflammatory response-related gene (IRRGs) and related competing endogenous RNA (ceRNA) network. We also utilized the Pearson’s correlation analysis to determine the correlation between IRRGs expression and tumor mutational burden (TMB), microsatellite instability (MSI), tumor-immune infiltration, and the drug sensitivity in NSCLC. Growth curve and Transwell assay used to verify the function of SNHG17 on NSCLC progression.

Results

First, we found that IRRGs were significantly upregulated in lung cancer, and its high expression was correlated with poor prognosis; high expression of IRRGs was significantly correlated with the tumor stage and poor prognosis in lung cancer patients. Moreover, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment indicated that these IRRGs are mainly involved in the inflammatory and immune response-related signaling pathway in the progression of NSCLC. We utilized 10 prognostic-related genes to construct a prognostic IRRGs model that could predict the overall survival of lung adenocarcinoma (LUAD) patients possessing high specificity and accuracy. Our evidence demonstrated that IRRGs expression was significantly correlated with the TMB, MSI, immune-cell infiltration, and diverse cancer-related drug sensitivity. Finally, we identified the upstream regulatory axis of IRRGs in NSCLC, namely, lncRNA MIR503HG/SNHG17/miR-330-3p/regulatory axis. Finally, knockdown of SNHG17 expression inhibited lung adenocarcinoma (LUAD) cell proliferation and migration. Our findings confirmed that SNHG17 is a novel oncogenic lncRNA and may be a biomarker for the prognosis and diagnosis of LUAD.

Conclusion

DNA hypomethylation/lncRNA MIR503HG/SNHG17/microRNA-330-3p/regulatory axis may be a valuable biomarker for prognosis and is significantly correlated with immune cell infiltration in lung cancer.

Bioinformatics and System Biology Approach to Reveal the Interaction Network and the Therapeutic Implications for Non-Small Cell Lung Cancer Patients With COVID-19

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the leading cause of coronavirus disease-2019 (COVID-19), is an emerging global health crisis. Lung cancer patients are at a higher risk of COVID-19 infection. With the increasing number of non-small-cell lung cancer (NSCLC) patients with COVID-19, there is an urgent need of efficacious drugs for the treatment of COVID-19/NSCLC.

Methods: Based on a comprehensive bioinformatic and systemic biological analysis, this study investigated COVID-19/NSCLC interactional hub genes, detected common pathways and molecular biomarkers, and predicted potential agents for COVID-19 and NSCLC.

Results: A total of 122 COVID-19/NSCLC interactional genes and 21 interactional hub genes were identified. The enrichment analysis indicated that COVID-19 and NSCLC shared common signaling pathways, including cell cycle, viral carcinogenesis, and p53 signaling pathway. In total, 10 important transcription factors (TFs) and 44 microRNAs (miRNAs) participated in regulations of 21 interactional hub genes. In addition, 23 potential candidates were predicted for the treatment of COVID-19 and NSCLC.

Conclusion: This study increased our understanding of pathophysiology and screened potential drugs for COVID-19 and NSCLC.

A systematic pan-cancer analysis identifies RIOK3 as an immunological and prognostic biomarker

OBJECTIVES

Despite recent research highlighting the critical function of RIO kinase 3 (RIOK3) in a variety of malignancies, a comprehensive evaluation of RIOK3 in human tumors is absent. Our study helps to clarify the molecular mechanism of RIOK3 in carcinogenesis from multiple perspectives.

METHODS

Our research looked into the potential oncogenic role of RIOK3 in 33 cancers using TCGA (The Cancer Genome Atlas), GTEx (Genotype-Tissue Expression Project), GEO (Gene Expression Omnibus) datasets, and several bioinformatics tools.

RESULTS

RIOK3 expression in tumors is disordered compared to normal tissue, and it is highly linked with the level of MMR (Mismatch repair) gene mutations and DNA methyltransferase expression. According to univariate survival analysis, it could be used as an independent prognostic factor. Further investigation demonstrated that RIOK3 expression was correlated with cancer-associated fibroblast, neutrophil, and endothelial infiltration levels in kidney cancer and was positively correlated with the expression of immune checkpoint markers in different cancers. The functional pathways of RIOK3 also included cell-cell adhesion, protein phosphorylation, and innate immune-related functions.

CONCLUSIONS

These findings suggest that RIOK3 could be used as an immunological and prognostic biomarker in various malignant tumors.

A Pan-Cancer Analysis Revealing the Dual Roles of Lysine (K)-Specific Demethylase 6B in Tumorigenesis and Immunity

Introduction: Epigenetic-targeted therapy has been increasingly applied in the treatment of cancers. Lysine (K)-specific demethylase 6B (KDM6B) is an epigenetic enzyme involved in the coordinated control between cellular intrinsic regulators and the tissue microenvironment whereas the pan-cancer analysis of KDM6B remains unavailable.

Methods: The dual role of KDM6B in 33 cancers was investigated based on the GEO (Gene Expression Omnibus) and TCGA (The Cancer Genome Atlas) databases. TIMER2 and GEPIA2 were applied to investigate the KDM6B levels in different subtypes or stages of tumors. Besides, the Human Protein Atlas database allowed us to conduct a pan-cancer study of the KDM6B protein levels. GEPIA2 and Kaplan–Meier plotter were used for the prognosis analysis in different cancers. Characterization of genetic modifications of the KDM6B gene was analyzed by the cBioPortal. DNA methylation levels of different KDM6B probes in different TCGA tumors were analyzed by MEXPRESS. TIMER2 was applied to determine the association of the KDM6B expression and immune infiltration and DNA methyltransferases. Spearman correlation analysis was used to assess the association of the KDM6B expression with TMB (tumor mutation burden) and MSI (microsatellite instability). The KEGG (Kyoto encyclopedia of genes and genomes) pathway analysis and GO (Gene ontology) enrichment analysis were used to further investigate the potential mechanism of KDM6B in tumor pathophysiology.

Results: KDM6B was downregulated in 11 cancer types and upregulated across five types. In KIRC (kidney renal clear cell carcinoma) and OV (ovarian serous cystadenocarcinoma), the KDM6B level was significantly associated with the pathological stage. A high level of KDM6B was related to poor OS (overall survival) outcomes for THCA (thyroid carcinoma), while a low level was correlated with poor OS and DFS (disease-free survival) prognosis of KIRC. The KDM6B expression level was associated with TMB, MSI, and immune cell infiltration, particularly cancer-associated fibroblasts, across various cancer types with different correlations. Furthermore, the enrichment analysis revealed the relationship between H3K4 and H3K27 methylation and KDM6B function.

Conclusion: Dysregulation of the DNA methyltransferase activity and methylation levels of H3K4 and H3K27 may involve in the dual role of KDM6B in tumorigenesis and development. Our study offered a relatively comprehensive understanding of KDM6B’s dual role in cancer development and response to immunotherapy.

Overexpression of galectin2 (LGALS2) predicts a better prognosis in human breast cancer

BACKGROUND

Galectins (LGALS) are a family of carbohydrate-binding proteins, and LGALS family members have shown prognostic roles in various types of cancers. However, the prognostic significance of some LGALS family members has not been studied in breast malignancy.

METHODS

The prognostic value of LGALS family mRNA expression in breast cancer patients was investigated according to distinct clinicopathological features (including lymph node, intrinsic subtype, pathological grade, HER2, and TP53 status) using the Kaplan-Meier plotter database. Quantitative real-time polymerase chain reaction and western blotting were used to detect the mRNA and protein expression of LGALS in breast cancer and normal breast cells. The aberrant expression of specific LGALS and its correlation with breast cancer outcomes remains elusive. In the present analysis, we comprehensively explored an immunohistochemistry-based map of protein expression profiles in normal tissues, cancer, and cell lines from the widely available Human Protein Atlas (HPA) database. Immunohistochemistry was applied to evaluate the expression of LGALS between cancer and normal tissues.

RESULTS

Our results showed that overexpression of LGALS2 mRNA were correlated with satisfactory overall survival among all breast cancer patients. Furthermore, LGALS2 and LGALS4 expression correlated with a better overall survival (OS) in grade III breast cancer patients; LGALS2 also predicted a better OS in basal-like subtype patients, luminal B patients, HER2-overexpressing patients, TP53 mutated and wild breast cancer patients. Notably, the mRNA and protein expression levels of LGALS2 were decreased in cancer cells compared with normal cells (P<0.05). Furthermore, LGALS2 expression in immunostaining score was lower in cancer tissues than in normal tissues (P<0.005).

CONCLUSION

In conclusion, LGALS2 has potential as a valuable biomarker for envisaging a satisfactory prognosis in patients with breast tumours, particularly those with luminal and basal B types, all stages and grade III tumours.

Comprehensive Analysis of SMC Gene Family Prognostic Value and Immune Infiltration in Patients With Pancreatic Adenocarcinoma

Pancreatic adenocarcinoma (PAAD) is a malignant tumor with high morbidity and mortality worldwide. Members from the structural maintenance of chromosomes (SMC) gene family function as oncogenes in various tumor types, but their roles in PAAD have not been elucidated. In this study, we aimed to explore the role of the SMC family in tumor progression and cancer immune infiltration in PAAD using integrative bioinformatic analyses. The results showed that the SMC 1A, 2, 3, 4, and 6 were overexpressed in PAAD tissues; of these, SMC 1A, 4, 5, and 6 could be potential prognostic biomarkers for PAAD. The expression of SMC genes was found to be strongly associated with immune cell infiltration. According to the infiltrative status of various immune cells, the mRNA expression of SMC genes in PAAD was associated with the overall and recurrence-free survival of patients. In conclusion, the SMC gene family is associated with PAAD and may be involved in tumorigenesis and cancer-immune interactions; thus, members from this gene family may serve as promising prognostic and therapeutic biomarkers of PAAD.

Abnormal spindle-like microcephaly-associated protein promotes proliferation by regulating cell cycle in epithelial ovarian cancer

BACKGROUND

Epithelial ovarian cancer (EOC) ranks first for female gynecological tumor-related deaths. Due to the limited efficacy of traditional chemotherapy strategies, potential therapeutic targets are urgently needed. Previous studies have reported a relationship between abnormal spindle-like microcephaly-associated protein (ASPM) and ovarian cancer based on immunohistochemistry (IHC) and bioinformatics analysis. However, the potential role of ASPM in the proliferation of ovarian cancer cells and its molecular mechanism remain to be elucidated. Therefore, we aimed to further investigate the potential role of ASPM and its underlying mechanism in EOC using integrated online databases, clinical samples, and cell models.

METHODS

We used online databases (Gene Expression Profiling Interactive Analysis, Cbioportal and Kaplan-Meier Plotter) to analyze differential ASPM expression in ovarian carcinoma and explore its prognostic value in ovarian cancer (OvCa) patients. Immunohistochemistry staining based on a clinical tissue microarray (TMA) comprised 75 cases of EOC tissue and 5 cases of adjacent normal ovary tissue was used to detect the ASPM expression and analyze the relationship between ASPM expression and EOC characteristics. Various cell function experiments related to tumorigenesis were performed including the CCK8 assay, 5-ethynyl-2'-deoxyuridine (EdU), colony formation assay and Transwell assay in EOC cell models (A2780 and OVCAR3) with knocked down ASPM by small interfering RNA (siRNA) to observe its role. Finally, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment was conducted to determine the signaling pathways in which ASPM was involved in the pathogenesis of ovarian cancer. Analysis of cell cycle distribution using flow cytometry was further performed to verify the pathways.

RESULTS

The expression profile based on data from The Cancer Genome Atlas (TCGA) database confirmed ASPM expression in EOC was higher compared with normal tissue, and further analysis suggested that higher expression was correlated with worse patient prognosis. Immunohistochemical analysis further indicated that ASPM was highly expressed in OvCa tissues and associated with a higher pathological stage, grade, and positive lymphatic metastasis. Cell models with knocked down ASPM by small interfering RNA (siRNA) significantly inhibited proliferation and migration. KEGG pathway enrichment and cell cycle analysis showed that ASPM silencing could inhibit ovarian cancer cell proliferation via synthesis (S) phase arrest.

CONCLUSIONS

Our study confirmed that ASPM promoted proliferation and caused S phase arrest in EOC cells. ASPM may become a potential molecular marker for early screening and a valuable therapeutic target in EOC.

KEYWORDS

Abnormal spindle-like microcephaly-associated protein (ASPM); epithelial ovarian cancer (EOC); prognosis; proliferation.

An integrated analysis of prognostic and immune infiltrates for hub genes as potential survival indicators in patients with lung adenocarcinoma

Objective

Lung adenocarcinoma (LUAD) is one of the major subtypes of lung cancer that is associated with poor prognosis. The aim of this study was to identify useful biomarkers to enhance the treatment and diagnosis of LUAD.

Methods

GEO2R was used to identify common up-regulated differentially expressed genes (DEGs) in the GSE32863, GSE40791, and GSE75037 datasets. The DEGs were submitted to Metascape for gene ontology and pathway enrichment analysis as well as construction of the protein-protein interaction (PPI) network, while the molecular complex detection (MCODE) plug-in was employed to filter important subnetworks. The expression levels of the hub genes and their prognostic values were evaluated using the UALCAN, GEPIA2, and Kaplan-Meier plotter databases. The timer algorithm was utilized to determine the correlation between immune cell infiltration and the expression levels of hub genes in LUAD tissues. In addition, the hub gene mutation landscape and the correlation analysis with tumor mutational burden (TMB) score were evaluated using maftools package and ggstatsplot package in R software, respectively.

Results

We identified 156 common up-regulated DEGs, with gene ontology and pathway enrichment analysis indicating that they were mostly enriched in mitotic cell cycle process and cell cycle pathway. DEGs in the subnetwork with the largest number of genes were AURKB, CCNB2, CDC20, CDCA5, CDCA8, CENPF, and KNTC1. The seven hub genes were highly expressed in LUAD tissues and were associated with poor prognosis. These hub genes were negatively correlated with most immune cells. The somatic mutation landscape showed that AURKB, CDC20, CENPF, and KNTC1 had mutations and were positively correlated with TMB scores.

Conclusions

Our findings demonstrate that increased expression of seven hub genes is associated with poor prognosis for LUAD patients. Additionally, the TMB score indicates that the high expression of hub gene increases immune cell infiltration in patients with lung adenocarcinoma which may significantly improve response to immunotherapy.

The Valuable Role of ARMC1 in Invasive Breast Cancer as a Novel Biomarker

Background

Invasive breast carcinoma (BRCA) is a common type of breast cancer with a high clinical incidence. Thus, it is significant to find effective biomarkers for BRCA diagnosis and treatment. Although some members of armadillo (ARM) repeat family of proteins are confirmed to be biomarkers in cancers, the role of armadillo repeat-containing 1 (ARMC1) in BRCA remains unknown.

Methods

We firstly analyzed the ARMC1 expression in normal breast tissues and BRCA samples and its association with overall survival by the public database. Next, the χ² test was used to evaluate the prognostic significance of ARMC1 expression in TCGA-BRCA patient samples. The ARMC1 mutations in BRCA were explored in the cBioportal database. Besides, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to explore the biological functions of ARMC1 in BRCA. Finally, immunohistochemistry and immunofluorescence staining were performed to validate the ARMC1 expression in BRCA.

Results

ARMC1 expression in tumor samples was significantly higher than that in normal tissues, and higher expression of ARMC1 was related to lower survival. Moreover, the tumor stage and histology of BRCA patients were associated with ARMC1 expression. ARMC1 genetic mutations occurred in 32% of BRCA patients, and the amplification and high expression of ARMC1 accounted for most of them. Furthermore, functional enrichment analysis suggested that ARMC1 might be involved in the cell cycle in BRCA. Ultimately, increased ARMC1 expression was found in clinical breast carcinoma tissues by our confirmatory experiments.

Conclusions

ARMC1 may play a significant role in BRCA and act as a biomarker, which provides valuable clues for the treatment and diagnosis of BRCA.

Downregulation of ZC3H13 by miR-362-3p/miR-425-5p is associated with a poor prognosis and adverse outcomes in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is notorious for its poor prognosis. Previous studies identified several N6-methyladenosine (m6A)-related genes that play key roles in the initiation and progression of HCC patients. In particular, the N6-methyladenosine RNA methylation regulator ZC3H13 could be a candidate as a novel biomarker and therapeutic target for hepatocellular carcinoma. In HCC, low expression of ZC3H13 was reported, but the molecular reason is unclear. In this study, we performed pan cancer analysis for ZC3H13 expression and prognosis using The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) data and found that ZC3H13 might be a potential tumor suppressor gene in HCC. Subsequently, miRNAs contributing to ZC3H13 downregulation were identified by a series of in silico analyses, including expression analysis, correlation analysis, and survival analysis. Finally, the miR-362-3p/miR-425-5p-ZC3H13 axis was identified as the most likely upstream miRNA-related pathway of ZC3H13 in HCC. Additionally, miR-362-3p/miR-425-5p mimic and inhibitor results were detected by quantitative real-time PCR (qPCR) analysis and western blotting. We identified an upstream regulatory mechanism of ZC3H13 in HCC, namely, the miR-362-3p/miR-425-5p-ZC3H13 axis. Moreover, the ZC3H13 level was significantly positively associated with tumor immune cell infiltration, biomarkers of immune cells, and immune checkpoint expression. Collectively, our findings elucidated that ncRNA-mediated downregulation of ZC3H13 was correlated with a poor prognosis and tumor immune infiltration in HCC. In conclusion, this study demonstrates that ZC3H13 is a direct target of miR-362-3p/miR-425-5p in liver hepatocellular carcinoma (LIHC) that regulates immune modulation in the microenvironment of LIHC.

An advanced network pharmacology study to explore the novel molecular mechanism of Compound Kushen Injection for treating hepatocellular carcinoma by bioinformatics and experimental verification

Background

Compound Kushen Injection (CKI) is a Chinese patent drug that exerts curative effects in the clinical treatment of hepatocellular carcinoma (HCC). This study aimed to explore the targets and potential pharmacological mechanisms of CKI in the treatment of HCC.

Methods

In this study, network pharmacology was used in combination with molecular biology experiments to predict and verify the molecular mechanism of CKI in the treatment of HCC. The constituents of CKI were identified by UHPLC-MS/MS and literature search. The targets corresponding to these compounds and the targets related to HCC were collected based on public databases. To screen out the potential hub targets of CKI in the treatment of HCC, a compound-HCC target network was constructed. The underlying pharmacological mechanism was explored through the subsequent enrichment analysis. Interactive Gene Expression Profiling Analysis and Kaplan-Meier plotter were used to examine the expression and prognostic value of hub genes. Furthermore, the effects of CKI on HCC were verified through molecular docking simulations and cell experiments in vitro.

Results

Network analysis revealed that BCHE, SRD5A2, EPHX2, ADH1C, ADH1A and CDK1 were the key targets of CKI in the treatment of HCC. Among them, only CDK1 was highly expressed in HCC tissues, while the other 5 targets were lowly expressed. Furthermore, the six hub genes were all closely related to the prognosis of HCC patients in survival analysis. Molecular docking revealed that there was an efficient binding potential between the constituents of CKI and BCHE. Experiments in vitro proved that CKI inhibited the proliferation of HepG2 cells and up-regulated SRD5A2 and ADH1A, while down-regulated CDK1 and EPHX2.

Conclusions

This study revealed and verified the targets of CKI on HCC based on network pharmacology and experiments and provided a scientific reference for further mechanism research.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12906-022-03530-3.

Comprehensive Analyses of the Immunological and Prognostic Roles of an IQGAP3AR/let-7c-5p/IQGAP3 Axis in Different Types of Human Cancer

IQ motif containing GTPase-activating protein 3 (IQGAP3) is a member of the Rho family of guanosine-5′-triphosphatases (GTPases). IQGAP3 plays a crucial part in the development and progression of several types of cancer. However, the prognostic, upstream-regulatory, and immunological roles of IQGAP3 in human cancer types are not known. We found that IQGAP3 expression was increased in different types of human cancer. The high expression of IQGAP3 was correlated with tumor stage, lymph node metastasis, and a poor prognosis in diverse types of human cancer. The DNA methylation of IQGAP3 was highly and negatively correlated with IQGAP3 expression in diverse cancer types. High DNA methylation in IQGAP3 was correlated with better overall survival in human cancer types. High mRNA expression of IQGAP3 was associated with tumor mutational burden, microsatellite instability, immune cell infiltration, and immune modulators. Analyses of signaling pathway enrichment showed that IQGAP3 was involved in the cell cycle. IQGAP3 expression was associated with sensitivity to a wide array of drugs in cancer cells lines. We revealed that polypyrimidine tract–binding protein 1 (PTBP1) and an IQGAP3-associated lncRNA (IQGAP3AR)/let-7c-5p axis were potential regulations for IQGAP3 expression. We provided the first evidence to show that an IQGAP3AR/let-7c-5p/IQGAP3 axis has indispensable roles in the progression and immune response in different types of human cancer.

Mapping Intellectual Structure for the Long Non-Coding RNA in Hepatocellular Carcinoma Development Research

Background: Emerging research suggests that long non-coding RNAs (lncRNAs) play an important role in a variety of developmental or physiological processes of hepatocellular carcinoma (HCC). Various differentially expressed lncRNAs have been identified in HCC. Thus, a deeper analysis of recent research concerning lncRNA and HCC development could provide scientists with a valuable reference for future studies.

Methods: Related publications were retrieved from the Web of Science Core Collection database. CiteSpace version 5.6.R4 was employed to conduct bibliometric analysis. Several network maps were constructed to evaluate the collaborations between different countries, institutions, authors, journals, and keywords.

Results: A total of 2,667 records were initially found from the year of 2010–2020. The annual related publications output had increased dramatically during these years. Although China was the most prolific country in terms of research publication, the United States played a leading role in collaborative network. The Nanjing Medical University was the most productive institute in the field of lncRNAs in HCC development. Gang Chen was the most prolific researcher, while Yang F was the most frequently co-cited author. Oncotarget, Cell, and Oncogene were the most highly co-cited journals. The most recent burst keywords were interaction, database, and pathway.

Conclusion: This study provides a comprehensive overview for the field of lncRNAs in HCC development based on bibliometric and visualized methods. The results would provide a reference for scholars focusing on this field.

Pan-Cancer Analysis Revealed SRSF9 as a New Biomarker for Prognosis and Immunotherapy

Background. Serine/arginine-rich splicing factor 9 (SRSF9) is one of the members of SRSF gene family and related to the tumorigenesis and the progression of tumor. However, whether SRSF9 has a crucial role across pan-cancer is still unknown. Methods. In this study, we used public databases, such as The Cancer Genome Atlas (TCGA), Cancer Cell Line Encyclopedia (CCLE), and Genotype-Tissue Expression (GTEx), to analyze SRSF9 expression level among tumor and normal cells. Survival analysis, K-M plotter, and PrognoScan were used to analyze the prognosis value of SRSF9, regarding to overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (PFI). Moreover, we performed the correlation between SRSF9 and clinical characteristics (including the outcome of prognosis), as well as molecular events of tumor mutation burden (TMB), microsatellite instability (MSI), immune checkpoint gene, tumor microenvironment (TME), immune infiltrating cells, mismatch repair (MMR) genes, m6A genes, DNA methyltransferases, and neoantigen with bioinformatics methods and TISIDB, TIMER, and Sangerbox websites. Results. In general, SRSF9 expression was upregulated in most cancers, such as BLCA, CHOL, and UCEC, which SRSF9 was associated with short survival and severe progression. In COAD, STAD, and UCEC, SRSF9 expression was positively related to both TMB and MSI. In BRCA, BLCA, ESCA, GBM, HNSC, LUSC, LUAD, OV, PRAD, TGCT, THCA, and UCEC, both immune score and stomal score showed a negative relationship with SRSF9 expression. Immune score showed a positive relationship with SRSF9 expression in LGG. SRSF9 expression had a significant and positive correlation with six types of immune infiltration cells in LGG, KIRC, LIHC, PCPG, PRAD, SKCM, THCA, and THYM, except in LUSC. In LIHC, SRSF9 was highly significant correlated with most immune checkpoint genes. For neoantigens, correlation between SRSF9 and the quantity of neoantigens was significantly positive in some cancer types. SRSF9 was also correlated with MMR genes, m6A genes, and DNA methyltransferases. In the 33 cancer types, gene set enrichment analysis (GSEA) demonstrated that SRSF9 was correlated with multiple functions and signaling pathways. Conclusion. These findings demonstrated that SRSF9 may be a new biomarker for the prognosis and immunotherapy in various cancers. As a result, it will be beneficial to provide new therapies for cancer patients, thereby improving the treatment and prognosis of cancer patients.

MicroRNA-133b Inhibits nTumor Cell Proliferation, Migration and Invasion by Targeting SUMO1 in Endometrial Carcinoma

Objectives: An increasing number of studies have confirmed that microRNAs (miRNAs/miRs), as oncogenes or tumor suppressor genes, play an important regulatory role in the occurrence and development of numerous types of cancer. The aim of the present study was to investigate the potential role and mechanism of miR-133b and small ubiquitin like modifier 1 (SUMO1) in the development of endometrial carcinoma (EC). Methods: First, Venn diagrams are used to identify the differential expressions of miRNAs in EC from GSE35794 and GSE25405 datasets. Next, we conduct a series of functional tests, including Cell Counting Kit-8, wound healing, and transwell and matrigel assays. Then, a bioinformatics tool, is used to identify downstream target genes of miR-133b and to verify the predicted results by RT-qPCR, Western blotting and double luciferase reporter gene analysis. Finally, in order to further study whether the cellular function of miR-133b is mediated by the expression of SUMO1, rescue experiments were carried out. Results: The results of bioinformatics studies showed that the expression of miR-133b was down-regulated in EC tissues, and the expression level of miR-133b was lower in patients with high grade, different histology or menopausal status. The results of functional assay showed that overexpression of miR-133b reduced cell proliferation, migration and invasion. On the contrary, miR-133b silence has the opposite effect. SUMO1 was the direct target of miR-133b and was negatively regulated by miR-133b. The decrease of SUMO1mRNA expression inhibited the proliferation, migration and invasion of EC cells, and reversed the effect of miR-133b on EC cells. Conclusion: The findings from the present study suggested that miR-133b may be a tumor suppressor gene and a potential therapeutic target for the treatment of EC.

Tricking enzymes in living cells: a mechanism-based strategy for design of DNA topoisomerase biosensors

Most activity-based molecular probes are designed to target enzymes that catalyze the breaking of chemical bonds and the conversion of a unimolecular substrate into bimolecular products. However, DNA topoisomerases are a class of enzymes that alter DNA topology without producing any molecular segments during catalysis, which hinders the development of practical methods for diagnosing these key biomarkers in living cells. Here, we established a new strategy for the effective sensing of the expression levels and catalytic activities of topoisomerases in cell-free systems and human cells. Using our newly designed biosensors, we tricked DNA topoisomerases within their catalytic cycles to switch on fluorescence and resume new rounds of catalysis. Considering that human topoisomerases have been widely recognized as biomarkers for multiple cancers and identified as promising targets for several anticancer drugs, we believe that these DNA-based biosensors and our design strategy would greatly benefit the future development of clinical tools for cancer diagnosis and treatment.

GPR116 overexpression correlates with poor prognosis in gastric cancer

The G protein-coupled receptor 116 (GPR116) is an adhesion subtype of the G protein-coupled receptor family and has been reported to be involved in tumorigenesis and cancer progression. Moreover, it has been shown to predict poor prognosis in breast and colorectal cancers. However, little is known about the role of GPR116 in gastric cancer (GC). In this study, we aimed to investigate the expression and clinical prognostic significance of GPR116 in GC.The mRNA expression levels of GPR116 in GC were analyzed using Gene Expression Omnibus and UALCAN databases, and GPR116 protein expression in GC tissues was detected using immunohistochemistry. The relationship between GPR116 expression and prognosis in patients with GC was analyzed and further validated using the Kaplan-Meier Plotter database. The correlation between GPR116 and the differentially expressed genes identified was analyzed using the LinkedOmics database. Gene set enrichment analysis was performed using WebGestalt. The results revealed that GPR116 expression was significantly upregulated in GC tissues, which was positively correlated with tumor node metastasis (TNM) staging and tumor invasion. Prognostic analysis suggested that high GPR116 expression contributed to poor overall survival in GC patients. Multivariate Cox analysis indicated that GPR116 overexpression was an independent prognostic indicator in patients with GC (HR = 1.855, 95% CI 1.021-3.370, P = .043). Enrichment analysis showed that GPR116 co-expression genes were mainly involved in extracellular matrix-receptor interaction, focal adhesion, cell adhesion, PI3K-Akt signaling, DNA replication, and cell cycle pathways. In conclusion, GPR116 was highly expressed in GC tissues and associated with poor prognosis in patients with GC, Thus GPR116 may be a novel prognostic marker and a potential therapeutic target for GC treatment.

Expression of Cyclin D1 gene in ovarian cancer and effect of silencing its expression on ovarian cancer cells based on the Oncomine database

We aimed to analyze the expression of Cyclin D1 (CCND1) gene in ovarian cancer and the influence of silencing its expression on ovarian cancer cells based on the Oncomine database. The expression of CCND1 gene in ovarian cancer was analyzed by utilizing the relevant information in different tumors and Oncomine database. The correlation between CCDN1 expression level and prognosis of ovarian cancer was analyzed by the online database Kaplan-Meier (kmplot.com). The expression of CCND1 gene in ovarian cancer and the effect of silencing its expression on cancer cells were analyzed by cell experiments. After mining and comprehensively analyzing 7 studies on the differential expression of CCND1 gene in ovarian cancer tissue and normal ovarian tissue included in the Oncomine database, it was found that the median value of CCND1 gene ranked 218.0 (P = 8.03 × 10^-6) among all differentially expressed genes, suggesting that CCND1 gene expression in ovarian cancer tissue was higher than that in normal ovarian tissue. Adib Ovarian, Bonome Ovarian and Hendrix Ovarian microarrays revealed that the expression of CCND1 gene in ovarian cancer tissue was significantly higher than that in normal ovarian tissue (P < 0.05). Kaplan-Meier Plotter database showed that the overall survival and progression-free survival of ovarian cancer patients with high CCND1 expression were significantly shorter than those of patients with low CCND1 expression (P < 0.05). The expression levels of CCND1 gene in normal ovarian epithelial cells and SKOV3 ovarian cancer cells were detected by RT-PCR. The expression of CCND1 gene was significantly higher in SKOV3 group than that in control group (P < 0.01). Flow cytometry revealed that the percentage of cells in G₀/G₁ phase was significantly higher, while that in S phase was lower in SKOV3 + siCCND1 group than the values of SKOV3 and SKOV3 + siNC groups (P < 0.05). The apoptosis rate of ovarian cancer cells was significantly higher in SKOV3 + siCCND1 group than those of SKOV3 and SKOV3 + siNC groups (P < 0.01). CCND1 gene is highly expressed in ovarian cancer tissue and related to prognosis. Preoperative evaluation of CCND1 gene expression in ovarian cancer patients may benefit the assessment of risk and prognosis.

Prognostic Value of Long Noncoding RNA DLEU2 and Its Relationship with Immune Infiltration in Kidney Renal Clear Cell Carcinoma and Liver Hepatocellular Carcinoma

Background

DLEU2 is a long noncoding RNA considered important in the progression of many cancers. However, correlations between DLEU2 and kidney renal clear cell carcinoma (KIRC) and liver hepatocellular carcinoma (LIHC) have rarely been reported.

Methods

We first analysed the expression of DLEU2 across cancers and the correlation between DLEU2 and the clinical features of KIRC and LIHC by using the “ggplot2” package in R and searched the Oncomine database and Timer website platform. We verified the expression of DLEU2 in the GEO dataset (GSE105261 and GSE45267). Receiver operating characteristic (ROC) curves were drawn using the “pROC” and “ggplot2” packages in R, and we constructed a DLEU2-based prognostic nomogram for KIRC and LIHC by using the “survival” and “rms” packages in R. Then, we analysed the correlation between DLEU2 expression and prognosis in R as well as the correlation between DLEU2 and immune cell infiltration in the TIMER database. Finally, we explored the causes of DLEU2 upregulation in the UCSC Xena and UALCAN databases.

Results

We found that DLEU2 was upregulated in many cancers, including KIRC and LIHC. Expression of DLEU2 is associated with tumour stage, grade, lymphatic metastasis, and distant metastasis in KIRC as well as alpha-fetoprotein (AFP), tumour stage, grade, lymphatic metastasis, and distant metastasis in LIHC. DLEU2 is an adverse factor for the prognosis of KIRC and LIHC. In addition, DLEU2 has moderate accuracy in diagnosing KIRC and LIHC and predicting their prognosis. Moreover, we found that expression of DLEU2 correlated positively with immune cell infiltration in KIRC and LIHC, and upregulation of DLEU2 in KIRC and LIHC suggests a poor prognosis based on immune cells analysis. Genetic and epigenetic analyses of DLEU2 indicate that copy number variations (CNVs) and methylation contribute to the upregulation of DLEU2.

Conclusion

The long noncoding RNA DLEU2 has the potential to predict the prognosis and immune infiltration of KIRC and LIHC.