scholarly journals Prediction of Lymph-Node Metastasis in Cancers Using Differentially Expressed mRNA and Non-coding RNA Signatures

2021 ◽  
Vol 9 ◽  
Author(s):  
Shihua Zhang ◽  
Cheng Zhang ◽  
Jinke Du ◽  
Rui Zhang ◽  
Shixiong Yang ◽  
...  
Keyword(s):  
Feature Selection ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Lymphatic Metastasis ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
Selection Strategy ◽  
Support Vector ◽  
Node Metastasis ◽  
Differentially Expressed Mrna

Accurate prediction of lymph-node metastasis in cancers is pivotal for the next targeted clinical interventions that allow favorable prognosis for patients. Different molecular profiles (mRNA and non-coding RNAs) have been widely used to establish classifiers for cancer prediction (e.g., tumor origin, cancerous or non-cancerous state, cancer subtype). However, few studies focus on lymphatic metastasis evaluation using these profiles, and the performance of classifiers based on different profiles has also not been compared. Here, differentially expressed mRNAs, miRNAs, and lncRNAs between lymph-node metastatic and non-metastatic groups were identified as molecular signatures to construct classifiers for lymphatic metastasis prediction in different cancers. With this similar feature selection strategy, support vector machine (SVM) classifiers based on different profiles were systematically compared in their prediction performance. For representative cancers (a total of nine types), these classifiers achieved comparative overall accuracies of 81.00% (67.96–92.19%), 81.97% (70.83–95.24%), and 80.78% (69.61–90.00%) on independent mRNA, miRNA, and lncRNA datasets, with a small set of biomarkers (6, 12, and 4 on average). Therefore, our proposed feature selection strategies are economical and efficient to identify biomarkers that aid in developing competitive classifiers for predicting lymph-node metastasis in cancers. A user-friendly webserver was also deployed to help researchers in metastasis risk determination by submitting their expression profiles of different origins.

scholarly journals Identification of lymph node metastasis-related microRNAs in lung adenocarcinoma and analysis of the underlying mechanisms using a bioinformatics approach

2016 ◽  
Vol 242 (7) ◽  
pp. 709-717 ◽  
Author(s):  
Li Yan ◽  
Demin Jiao ◽  
Huizhen Hu ◽  
Jian Wang ◽  
Xiali Tang ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Lung Adenocarcinoma ◽  
Lymphatic Metastasis ◽  
Target Genes ◽  
Bioinformatics Analyses ◽  
Node Metastasis ◽  
Primary Lung Adenocarcinoma ◽  
Underlying Mechanisms

This study aimed to screen lymphatic metastasis-related microRNAs (miRNAs) in lung adenocarcinoma and explore their underlying mechanisms using bioinformatics. The miRNA expression in primary lung adenocarcinoma, matched adjacent non-tumorigenic and lymph node metastasis tissues of patients were profiled via microarray. The screened metastasis-related miRNAs were then validated using quantitative real-time PCR in a second cohort of lung adenocarcinoma patients with lymphatic metastasis. Significance was determined using a paired t-test. Target genes of the metastasis-related miRNAs were predicted using TargetScan, and transcription factors (TFs) were predicted based on the TRANSFAC and ENCODE databases. Furthermore, the related long non-coding RNAs (lncRNAs) were screened with starBase v2.0. The miRNA-TF-mRNA and lncRNA-miRNA-mRNA networks were constructed to determine the key interactions associated with lung adenocarcinoma metastasis. According to the miRNA microarray results, there were 10 miRNAs that were differentially expressed in metastatic tissues compared with primary tumor and adjacent non-tumorigenic tissues. Among them were increased levels of miR-146a-5p, miR-342-3p, and miR-150-5p, which were validated in the second cohort. Based on the miRNA-TF-mRNA network, vascular endothelial growth factor A and transcription factors (TFs) including TP53, SMAD4, and EP300 were recognized as critical targets of the three miRNAs. Interactions involving SNHG16–miR-146a-5p–SMAD4 and RP6-24A23.7–miR-342-3p/miR-150-5p–EP300 were highlighted according to the lncRNA-miRNA-mRNA network. miR-146a-5p, miR-342-3p, and miR-150-5p are lymphatic metastasis-related miRNAs in lung adenocarcinoma. Bioinformatics analyses demonstrated that SNHG16 might inhibit the interaction between miR-146a-5p and SMAD4, while RP6-24A23.7 might weaken miR-342-3p–EP300 and miR-150-5p–EP300 interactions in metastasis.

Initial study of microRNA expression profiles of colonic cancer without lymph node metastasis

2010 ◽  
Vol 11 (1) ◽  
pp. 50-54 ◽  
Author(s):  
Ying Xin WANG ◽  
Xiao Yan ZHANG ◽  
Bao Feng ZHANG ◽  
Chang Qing YANG ◽  
Xi Mei CHEN ◽  
...  
Keyword(s):  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Colonic Cancer ◽  
Expression Profiles ◽  
Initial Study ◽  
Microrna Expression ◽  
Node Metastasis

scholarly journals Expression profiles of non-small cell lung cancers on cDNA microarrays: Identification of genes for prediction of lymph-node metastasis and sensitivity to anti-cancer drugs

Oncogene ◽  
2003 ◽  
Vol 22 (14) ◽  
pp. 2192-2205 ◽  
Author(s):  
Takefumi Kikuchi ◽  
Yataro Daigo ◽  
Toyomasa Katagiri ◽  
Tatsuhiko Tsunoda ◽  
Koichi Okada ◽  
...  
Keyword(s):  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Expression Profiles ◽  
Cdna Microarrays ◽  
Small Cell ◽  
Cancer Drugs ◽  
Small Cell Lung ◽  
Lung Cancers ◽  
Node Metastasis ◽  
Anti Cancer

scholarly journals Identification of the miRNA signature and key genes in colorectal cancer lymph node metastasis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xi Wang ◽  
Guangyu Gao ◽  
Zhengrong Chen ◽  
Zhihao Chen ◽  
Mingxiao Han ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Expression Profiles ◽  
Bioinformatic Analysis ◽  
The Cancer Genome Atlas ◽  
Node Metastasis ◽  
Novel Mirna ◽  
Potential Biomarker

Abstract Background Because its metastasis to the lymph nodes are closely related to poor prognosis, miRNAs and mRNAs can serve as biomarkers for the diagnosis, prognosis, and therapy of colorectal cancer (CRC). This study aimed to identify novel gene signatures in the lymph node metastasis of CRC. Methods GSE56350, GSE70574, and GSE95109 datasets were downloaded from the Gene Expression Omnibus (GEO) database, while data from 569 colorectal cancer cases were also downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed miRNAs (DE-miRNAs) were calculated using R programming language (Version 3.6.3), while gene ontology and enrichment analysis of target mRNAs were performed using FunRich (http://www.funrich.org). Furthermore, the mRNA–miRNA network was constructed using Cytoscape software (Version 3.8.0). Gene expression levels were verified using the GEO datasets. Similarly, quantitative real-time PCR (qPCR) was used to examine expression profiles from 20 paired non-metastatic and metastatic lymph node tissue samples obtained from patients with CRC. Results In total, five DE-miRNAs were selected, and 34 mRNAs were identified after filtering the results. Moreover, two key miRNAs (hsa-miR-99a, hsa-miR-100) and one gene (heparan sulfate-glucosamine 3-sulfotransferase 2 [HS3ST2]) were identified. The GEO datasets analysis and qPCR results showed that the expression of key miRNA and genes were consistent with that obtained from the bioinformatic analysis. A novel miRNA–mRNA network capable of predicting the prognosis and confirmed experimentally, hsa-miR-99a-HS3ST2-hsa-miR-100, was found after expression analysis in metastasized lymph node tissue from CRC samples. Conclusion In summary, miRNAs and genes with potential as biomarkers were found and a novel miRNA–mRNA network was established for CRC lymph node metastasis by systematic bioinformatic analysis and experimental validation. This network may be used as a potential biomarker in the development of lymph node metastatic CRC.

scholarly journals Fucose mutarotase is differentially expressed in lymph node metastasis in human breast cancer.

2021 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Breast Cancer ◽  
Metastatic Breast Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Metastatic Breast ◽  
Lymphoid Organ ◽  
Differentially Expressed ◽  
Primary Tumors ◽  
Node Metastasis ◽  
The Brain

Metastasis to the brain is a clinical problem in patients with breast cancer (1-3). Between the breast and the brain reside the secondary lymphoid organ, the lymph nodes. We mined published microarray data (4, 5) to compare primary and metastatic tumor transcriptomes for the discovery of genes associated with lymph node metastasis in humans with metastatic breast cancer. We found that fucose mutarotase, encoded by FUOM, was among the genes whose expression was most different in the lymph node metastases of patients with metastatic breast cancer as compared to primary tumors of the breast. Analysis of a separate microarray dataset revealed that FUOM was also differentially expressed in brain metastatic tissues (5). FUOM mRNA was present at increased quantities in lymph node metastatic tissues as compared to primary tumors of the breast. Expression of FUOM in primary tumors was correlated with patient overall survival in lymph node positive patients but not in lymph node negative patients. Modulation of FUOM expression may be relevant to the biology by which tumor cells metastasize from the breast to the lymph node in humans with metastatic breast cancer.

scholarly journals COMP is differentially expressed in lymph node metastasis in human breast cancer.

2021 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Breast Cancer ◽  
Metastatic Breast Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Lymph Nodes ◽  
Metastatic Breast ◽  
Differentially Expressed ◽  
Primary Tumors ◽  
Node Metastasis ◽  
The Brain

Metastasis to the brain is a clinical problem in patients with breast cancer (1-3). Between the breast and the brain reside the secondary lymphoid organ, the lymph nodes. We mined published microarray data (4, 5) to compare primary and metastatic tumor transcriptomes for the discovery of genes associated with lymph node metastasis in humans with metastatic breast cancer. We found that cartilage oligomeric matrix protein, encoded by COMP, was among the genes whose expression was most different in the lymph node metastases of patients with metastatic breast cancer as compared to primary tumors of the breast. Analysis of a separate microarray dataset revealed that COMP was also differentially expressed in brain metastatic tissues5. COMP mRNA was present at increased quantities in lymph node metastatic tissues as compared to primary tumors of the breast. Expression of COMP in primary tumors was correlated with patient recurrence-free survival in lymph node negative patients but not in lymph node positive patients. Modulation of COMP expression may be relevant to the biology by which tumor cells metastasize from the breast to the lymph nodes in humans with metastatic breast cancer.

scholarly journals PTPRCAP is differentially expressed in lymph node metastasis in human breast cancer.

2021 ◽  
Author(s):  
Shahan Mamoor
Keyword(s):  
Breast Cancer ◽  
Metastatic Breast Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Lymph Nodes ◽  
Metastatic Breast ◽  
Differentially Expressed ◽  
Primary Tumors ◽  
Node Metastasis ◽  
The Brain

Metastasis to the brain is a clinical problem in patients with breast cancer (1-3). Between the breast and the brain reside the secondary lymphoid organ, the lymph nodes. We mined published microarray data (4, 5) to compare primary and metastatic tumor transcriptomes for the discovery of genes associated with lymph node metastasis in humans with metastatic breast cancer. We found that protein tyrosine phosphatase, receptor type C associated protein, encoded by PTPRCAP, was among the genes whose expression was most different in the lymph node metastases of patients with metastatic breast cancer as compared to primary tumors of the breast. Analysis of a separate microarray dataset revealed that PTPRCAP was also differentially expressed in brain metastatic tissues5. PTPRCAP mRNA was present at increased quantities in lymph node metastatic tissues as compared to primary tumors of the breast. Expression of PTPRCAP in primary tumors was correlated with patient distant metastasis-free survival in lymph node negative patients but not in lymph node positive patients. Modulation of PTPRCAP expression may be relevant to the biology by which tumor cells metastasize from the breast to the lymph nodes in humans with metastatic breast cancer.

scholarly journals In-silico analysis of differentially expressed genes and their regulating microRNA involved in lymph node metastasis in invasive breast carcinoma

2020 ◽  
Author(s):  
Anupama Modi ◽  
Purvi Purohit ◽  
Ashita Gadwal ◽  
Shweta Ukey ◽  
Dipayan Roy ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Candidate Genes ◽  
Differentially Expressed Genes ◽  
In Silico ◽  
Nodal Metastasis ◽  
Differentially Expressed ◽  
Hub Genes ◽  
Node Metastasis

AbstractIntroductionAxillary nodal metastasis is related to poor prognosis in breast cancer (BC). The metastatic progression in BC is related to molecular signatures. The currently popular methods to evaluate nodal status may give false negatives or give rise to secondary complications. In this study, key candidate genes in BC lymph node metastasis have been identified from publicly available microarray datasets and their roles in BC have been explored through survival analysis and target prediction.MethodsGene Expression Omnibus datasets have been analyzed for differentially expressed genes (DEGs) in lymph node-positive BC patients compared to nodal-negative and healthy tissues. The functional enrichment analysis was done in database for annotation, visualization and integrated discovery (DAVID). Protein-protein interaction (PPI) network was constructed in Search Tool for the Retrieval of Interacting Genes and proteins (STRING) and visualized on Cytoscape. The candidate hub genes were identified and their expression analyzed for overall survival (OS) in Gene Expression Profiling Interactive Analysis (GEPIA). The target miRNA and transcription factors were analyzed through miRNet.ResultsA total of 102 overlapping DEGs were found. Gene Ontology revealed eleven, seventeen, and three significant terms for cellular component, biological process, and molecular function respectively. Six candidate genes, DSC3, KRT5, KRT6B, KRT17, KRT81, and SERPINB5 were significantly associated with nodal metastasis and OS in BC patients. A total of 83 targeting miRNA were identified through miRNet and hsa-miR-155-5p was found to be the most significant miRNA which was targeting five out of six hub genes.ConclusionIn-silico survival and expression analyses revealed six candidate genes and 83 miRNAs, which may be potential diagnostic markers and therapeutic targets in BC patients and miR-155-5p shows promise as it targeted five important hub genes related to lymph-node metastasis.

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