CA : A Cancer Journal for Clinicians

Background: Papillary thyroid cancer (PTC) is the most common subtype of thyroid cancer, and inflammation relates significantly to its initiation and prognosis. Systematic exploration of the immunogenomic landscape therein to assist in PTC prognosis is therefore urgent. The Cancer Genome Atlas (TCGA) project provides a large number of genetic PTC samples that enable a comprehensive and reliable immunogenomic study.

Methods: We integrated the expression profiles of immune-related genes (IRGs) and progression-free intervals (PFIs) in survival in 493 PTC patients based on the TCGA dataset. Differentially-expressed and survival-associated IRGs in PTC patients were estimated a computational difference algorithm and COX regression analysis. The potential molecular mechanisms and properties of these PTC-specific IRGs were also explored with the help of computational biology. A new prognostic index based on immune-related genes was developed by using multivariable COX analysis.

Results: A total of 46 differentially expressed immune-related genes were significantly correlated with clinical outcome of PTC patients. Functional enrichment analysis revealed that these genes were actively involved in a cytokine-cytokine receptor interaction KEGG pathway. A prognostic signature based on RGs (AGTR1, CTGF, FAM3B, IL11, IL17C, PTH2R and SPAG11A) performed moderately in prognostic predictions and correlated with age, tumor stage, metastasis, number of lesions, and tumor burden. Intriguingly, the prognostic index based on IRGs reflected infiltration by several types of immune cells.

Conclusions: Together, our results screened several IRGs of clinical significance, revealed drivers of the immune repertoire, and demonstrated the importance of a personalized, IRG-based immune signature in the recognition, surveillance, and prognosis of PTC.

/pdf/development-of-a-prognostic-index-based-on-an-immunogenomic-1bv8crsss0.pdf

Development of a prognostic index based on an immunogenomic landscape analysis of papillary thyroid cancer

MicroRNAs as major regulators of the autophagy pathway

Background: Topoisomerase IIA (TOP2A) gene encodes DNA topoisomerase enzyme and has been reported that TOP2A is broadly expressed in many types of cancers. Our study aims to investigate the prognostic effect of TOP2A on lung adenocarcinoma (LUAD) and the potential molecular mechanism of TOP2A to tumorigenesis. Methods: Bioinformatical analysis, real-time PCR and Western blot were applied to explore the expression level of TOP2A. Kaplan-Meier survival analysis was used to evaluate the effect of TOP2A on patients' prognosis. Cell proliferation, migration and invasion ability were examined by colony-formation, Cell Counting Kit-8 (CCK8) assay, wound healing assay and transwell invasion assay, respectively. Results: We firstly investigated differentially expressed genes in lung adenocarcinoma and normal tissues of GEO (tumor = 666, normal = 184) and TCGA (tumor = 517, normal = 59) and these data showed that TOP2A is broadly expressed in LUAD and the expression level of TOP2A is associated with poor prognosis, which indicated that TOP2A is an upregulated prognostic related gene in LUAD. Then we identified that the expression level of TOP2A was upregulated in both surgically removed lung cancer tissues and lung cancer cell lines. Knockdown of TOP2A in A549 and GLC82 cells inhibited cell proliferation, migration and invasion. Inhibition of TOP2A reduced the expression levels of CCNB1 and CCNB2, which indicated that TOP2A targeting CCNB1 and CCNB2 promotes GLC82 and A549 cells proliferation and metastasis. Conclusions: Our study revealed an important role of TOP2A in LUAD, and may provide a potential prognostic indicator and target for cancer therapy.

/pdf/top2a-promotes-lung-adenocarcinoma-cells-malignant-5dh3l9eew5.pdf

TOP2A Promotes Lung Adenocarcinoma Cells' Malignant Progression and Predicts Poor Prognosis in Lung Adenocarcinoma.

Liver cancer is among top deadly cancers worldwide with a very poor prognosis, and the liver is a vulnerable site for metastases of other cancers. Early diagnosis is crucial for treatment of the predominant liver cancers, namely hepatocellular carcinoma (HCC). Here we developed a novel computational framework for the stage-specific analysis of HCC. Using publicly available clinical and RNA-Seq data of cancer samples and controls and the AJCC staging system, we performed a linear modelling analysis of gene expression across all stages and found significant genome-wide changes in the log fold-change of gene expression in cancer samples relative to control. To identify genes that were stage-specific controlling for confounding differential expression in other stages, we developed a set of six pairwise contrasts between the stages and enforced a p-value threshold (< 0.05) for each such contrast. Genes were specific for a stage if they passed all the significance filters for that stage. The monotonicity of gene expression with cancer progression was analyzed with a linear model using the cancer stage as a numeric variable. Our analysis yielded two stage-I specific genes (CA9, WNT7B), two stage-II specific genes (APOBEC3B, FAM186A), ten stage-III specific genes including DLG5, PARI, NCAPG2, GNMT and XRCC2, and 35 stage-IV specific genes including GABRD, PGAM2, PECAM1 and CXCR2P1. Overexpression of DLG5 was found to be tumor-promoting contrary to the cancer literature on this gene. Further, GABRD was found to be signifincantly monotonically upregulated across stages. Our work has revealed 1977 genes with significant monotonic patterns of expression across cancer stages. NDUFA4L2, CRHBP and PIGU were top genes with monotonic changes of expression across cancer stages that could represent promising targets for therapy. Comparison with gene signatures from the BCLC staging system identified two genes, HSP90AB1 and ARHGAP42. Gene set enrichment analysis indicated overrepresented pathways specific to each stage, notably viral infection pathways in HCC initiation. Our study identified novel significant stage-specific differentially expressed genes which could enhance our understanding of the molecular determinants of hepatocellular carcinoma progression. Our findings could serve as biomarkers that potentially underpin diagnosis as well as pinpoint therapeutic targets.

/pdf/novel-significant-stage-specific-differentially-expressed-4oinyikk3e.pdf

Novel significant stage-specific differentially expressed genes in hepatocellular carcinoma.

BACKGROUND Liver hepatocellular carcinoma accounts for the overwhelming majority of primary liver cancers and its belated diagnosis and poor prognosis call for novel biomarkers to be discovered, which, in the era of big data, innovative bioinformatics and computational techniques can prove to be highly helpful in. METHODS Big data aggregated from The Cancer Genome Atlas and Natural Language Processing were integrated to generate differentially expressed genes. Relevant signaling pathways of differentially expressed genes went through Gene Ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes and Panther pathway enrichment analysis and protein-protein interaction network. The pathway ranked high in the enrichment analysis was further investigated, and selected genes with top priority were evaluated and assessed in terms of their diagnostic and prognostic values. RESULTS A list of 389 genes was generated by overlapping genes from The Cancer Genome Atlas and Natural Language Processing. Three pathways demonstrated top priorities, and the one with specific associations with cancers, 'pathways in cancer,' was analyzed with its four highlighted genes, namely, BIRC5, E2F1, CCNE1, and CDKN2A, which were validated using Oncomine. The detection pool composed of the four genes presented satisfactory diagnostic power with an outstanding integrated AUC of 0.990 (95% CI [0.982-0.998], P < 0.001, sensitivity: 96.0%, specificity: 96.5%). BIRC5 (P = 0.021) and CCNE1 (P = 0.027) were associated with poor prognosis, while CDKN2A (P = 0.066) and E2F1 (P = 0.088) demonstrated no statistically significant differences. DISCUSSION The study illustrates liver hepatocellular carcinoma gene signatures, related pathways and networks from the perspective of big data, featuring the cancer-specific pathway with priority, 'pathways in cancer.' The detection pool of the four highlighted genes, namely BIRC5, E2F1, CCNE1 and CDKN2A, should be further investigated given its high evidence level of diagnosis, whereas the prognostic powers of BIRC5 and CCNE1 are equally attractive and worthy of attention.

/pdf/from-big-data-to-diagnosis-and-prognosis-gene-expression-1abivkm630.pdf

From big data to diagnosis and prognosis: gene expression signatures in liver hepatocellular carcinoma.

Background/aims Accumulating evidence strongly suggests that microRNAs (miRNAs) modulate the expression of known tumor suppressor genes and oncogenes. In the present study, we found that the proliferation and invasion ability of pancreatic ductal adenocarcinoma (PDAC) cells were significantly suppressed by the overexpression of miR-23b-3p. In addition, there are miR-23b-3p binding sites in annexin A2 (ANXA2). Here, we investigated whether miR-23b-3p had an impact on the progression and metastasis of PDAC by targeting ANXA2. Methods Cell proliferation, migration, and invasion, and cell cycle assays were performed to explore the effect of miR-23b-3p on various malignant phenotypes of pancreatic cancer cells. The size of tumors was observed following miR-23b-3p overexpression in an in vivo chick chorioallantoic membrane assay. Dual-luciferase reporter, quantitative real-time PCR, western blot, and immunohistochemical analyses were used to validate the relationship between miR-23b-3p and ANXA2 in vitro. Results We observed that miR-23b-3p could bind specifically to the 3' untranslated region of ANXA2 and inhibit its expression. MiR-23b-3p overexpression downregulated the expression of ANXA2 mRNA in PDAC cells and limited the size of tumors or even prevented tumor formation. In addition, there was a negative correlation between miR-23b-3p expression and ANXA2 protein expression in clinical specimens. Conclusion MiR-23b-3p inhibits the development and progression of PDAC by regulating ANXA2 directly.

/pdf/biological-effect-and-mechanism-of-the-mir-23b-3p-anxa2-axis-11aih4tceq.pdf

Biological Effect and Mechanism of the miR-23b-3p/ANXA2 Axis in Pancreatic Ductal Adenocarcinoma.

Background/Aims: MicroRNAs participate in various biological processes in malignant tumors. However, the mechanisms of miR-224-5p in digestive system cancers are not fully understood. A comprehensive investigation of the clinical value and potential targets of miR-224-5p in cancers of the digestive tract is necessary. Methods: Expression profiling data and related-prognostic data of miR-224-5p were acquired from Gene Expression Omnibus, The Cancer Genome Atlas, ArrayExpress, and published literature. The potential target mRNAs of miR-224-5p were predicted using bioinformatics methods and finally annotated using Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Results: MiR-224-5p is up-regulated in digestive system cancers (SMD=0.69, 95% CI: 0.43-0.96, P<0.0001) and exhibits a moderate diagnostic ability (AUC=0.84, 95% CI: 0.80-0.87). Our data also demonstrated that miR-224-5p is statistically significantly correlated with overall survival univariate analysis (HR=1.69, 95% CI: 1.15-2.49, P=0.007) and multivariate analysis (HR=2.39, 95% CI: 1.74-3.30, P<0.0001). In total, 388 potential miR-224-5p target mRNAs were predicted by bioinformatics methods. GO annotation analysis revealed that the top terms of miR-224-5p in biological process, cellular component and molecular function were system development, neuron part, and transcriptional activator activity, RNA polymerase II core promoter proximal region sequence-specific binding, respectively. Moreover, eight pathways were identified in KEGG pathway enrichment analysis. Conclusions: MiR-224-5p is up-regulated and has the potential to become a diagnostic and prognostic biomarker in digestive system cancers. MiR-224-5p might play vital roles in cancers of the digestive tract but the exact molecular mechanisms need further study and verification.

/pdf/potential-targets-and-clinical-value-of-mir-224-5p-in-4lkhh7bofz.pdf

Potential Targets and Clinical Value of MiR-224-5p in Cancers of the Digestive Tract.

Objective: To enquire into the clinical significance and potential molecular mechanism of microRNA (miRNA)-196b-5p in hepatocellular carcinoma (HCC).

Methods: Quantitative reverse transcription and polymerase chain reaction (qRT-PCR) were utilized to examine miR-196b-5p expression level in 67 HCC paraffin embedded tissues and corresponding adjacent tissues. Correlations of miR-196b-5p expression level with clinicopathological characteristics were analyzed in our study. The expression level and clinical significance of miR-196b-5p in HCC were also evaluated in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. We made predictions of the target genes of miR-196b-5p by twelve online software and then selected genes predicted by at least 5 software. Subsequently, in order to obtain the potential target genes of miR-196b-5p, we overlapped the predicted target genes and down-regulated mRNAs in HCC based on TCGA database. Then, we performed the Gene Ontology (GO) and the Disease Ontology (DO) functional annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and Protein-Protein Interaction (PPI) network construction of those miR-196b-5p potential target genes.

Results: Higher expression level of miR-196b-5p was seen in HCC tissues than in the corresponding adjacent tissues based on qRT-PCR (P = 0.0007). The expression level of miR-196b-5p was linked with tumor size (P = 0.03), tumor node (P = 0.024), vascular invasion (P = 0.029) and capsular invasion (P = 0.026) in HCC patients. Comprehensive meta-analysis of miR-196b-5p expression based on TCGA, GEO and qRT-PCR verified that higher expression level of miR-196b-5p was observed in HCC tissues than in normal control liver tissues (SMD = 0.56, 95%CI: 0.39-0.72, P heterogeneity = 0.275, I2 = 18.3%). GO annotation revealed that the top terms in biological process, cellular component and molecular function were single-organism catabolic process, neuronal cell body and transmembrane receptor protein kinase activity, respectively. The most relevant disease in DO annotation was arteriosclerosis. The tryptophan metabolism pathway ranked first in KEGG pathway enrichment analysis. The PPI network showed that IGF1, FOXO1, AR and FOS were mostly likely to become the core genes of miR-196b-5p potential target genes, which however required further experiments for validation.

Conclusion: The miR-196b-5p was observed to show higher expression in HCC tissues than in normal control liver tissues. Moreover, the miR-196b-5p expression level had correlations with the clinicopathological parameters such as vascular invasion of HCC, but the molecular mechanisms of miR-196b-5p in HCC still need further elucidation and verification.

/pdf/clinical-significance-of-microrna-196b-5p-in-hepatocellular-5807ytle8x.pdf

Clinical Significance of microRNA-196b-5p in Hepatocellular Carcinoma and its Potential Molecular Mechanism.

OBJECTIVE To explore potential targets and clinical value of miR-490-5p in the oncogenesis and progression of hepatocellular carcinoma (HCC). METHODS Clinical value of miR-490-5p was accessed through The Cancer Genome Atlas (TCGA) and qRT-PCR analyses. Potential target mRNAs of miR-490-5p were predicted by bioinformatics methods and were annotated as Gene Ontology (GO) function analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway analysis, and Protein-Protein Interaction (PPI) network analysis. RESULTS miR-490 expression in HCC tissues was lower compared with normal control tissues based on TCGA and down regulation of miR-490-5p was verified by qRT-PCR (P<0.0001). Both miR-490 and miR-490-5p had moderate ability to diagnose HCC tissues from noncancerous tissues. Moreover, lower miR-490 level predicted poorer overall survival in patients with HCC (P=0.0063). One hundred and eighty-four mRNAs were selected as potential targets of miR-490-5p by overlap with 4,090 prediction genes and 1,478 differentially expressed genes (DEGs). Gene Ontology (GO) function analysis showed that the most significant terms were vasculature development, endoplasmic reticulum, and protein binding in biological process (BP), cellular component (CC), and molecular function (MF). In KEGG signaling pathway analysis, the statistically significant terms were lysosome, focal adhesion, glioma. In PPI network analysis, SRC, SRP9, PDGFRB, RPL28, and RPS23 were identified as the hub genes. CONCLUSION miR-490-5p is down-regulated in HCC and may be a prospectively diagnostic and prognostic biomarker. Moreover, miR-490-5p might directly target SRC, SRP9, PDGFRB, RPL28, or RPS23 and play an important role in HCC.

Potential targets and clinical value of miR-490-5p in hepatocellular carcinoma: a study based on TCGA, qRT-PCR and bioinformatics analyses.

Popular Tasks used by Researchers

How can I help with your research?

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

We encountered an error while loading the panel. Please try refreshing the page.

Something went wrong

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

Anyone with the link can view this chat. You can switch it back to private anytime.

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Lu Zhang

Author Tools

Chat about Author