Gene Expression of Mesenchyme Forkhead 1 (FOXC2) Significantly Correlates With the Degree of Lymph Node Metastasis in Colorectal Cancer

Abstract In stage III colorectal cancer, patients with N1 stage tumors show poorer outcome than patients with N2 stage tumors. Our objective was to identify genes that are predictive for the presence of lymph node metastasis, and to characterize the aggressiveness of lymph node metastases. Gene expression profiles of colorectal cancer were determined by microarray in training (n = 116) and test (n = 25) sets of patients. We identified 40 discriminating probes in patients with and without lymph node metastases. Using these probes, we could predict the presence of lymph node metastasis with an accuracy of 87.1% (training set) and 76.0% (test set). Among discriminating probes, FOXC2 expression was significantly correlated with the degree of lymph node metastasis. FOXC2 was expressed significantly and disparately in patients with N1 and N2 stage tumors as analyzed by real-time reverse transcriptase–polymerase chain reaction. FOXC2 appears to be involved in determining the aggressiveness of lymph node metastasis in colorectal cancer.

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Prediction of Lymph Node Metastasis with Use of Artificial Neural Networks Based on Gene Expression Profiles in Esophageal Squamous Cell Carcinoma

Annals of Surgical Oncology ◽

10.1245/aso.2004.03.007 ◽

2004 ◽

Vol 11 (12) ◽

pp. 1070-1078 ◽

Cited By ~ 39

Author(s):

Takatsugu Kan ◽

Yutaka Shimada ◽

Fumiaki Sato ◽

Tetsuo Ito ◽

Kan Kondo ◽

...

Keyword(s):

Gene Expression ◽

Neural Networks ◽

Squamous Cell Carcinoma ◽

Artificial Neural Networks ◽

Lymph Node ◽

Lymph Node Metastasis ◽

Esophageal Squamous Cell Carcinoma ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Node Metastasis

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Siglec-15 Is an Immune Suppressor and Potential Target for Immunotherapy in the Pre-Metastatic Lymph Node of Colorectal Cancer

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.691937 ◽

2021 ◽

Vol 9 ◽

Author(s):

Hang Du ◽

Jingling Tang ◽

Xiaoyun Li ◽

Xinjun Wang ◽

Liyun Wu ◽

...

Keyword(s):

Gene Expression ◽

Colorectal Cancer ◽

Lymph Node ◽

Lymph Node Metastasis ◽

Lymph Nodes ◽

Metastatic Lymph Node ◽

Sentinel Lymph Nodes ◽

Node Metastasis ◽

Metastatic Lymph ◽

Colorectal Cancer Patients

Lymph node metastasis indicates a poor prognosis in colorectal cancer. To better understand the underlying mechanisms of lymph node metastasis, we analyzed transcriptome characteristics of the pre-metastatic lymph node, a putative microenvironment favorable for the seeding and proliferation of cancer cells. Thus, we tried to compare and elucidate the transcriptional and immune characteristics of sentinel lymph nodes (SNs) with matched non-sentinel lymph nodes (NSNs) in colorectal cancer patients. In this study, a total of 38 pairs of SNs and NSNs were collected, in which 26 pairs of non-metastatic lymph nodes were subjected to RNA-seq and bioinformatics analysis for the gene expression profiles. There were 16 differentially expressed genes between SNs and NSNs being identified, including 9 upregulated and 7 downregulated genes in SN. Gene Ontology (GO) classification analysis revealed that the differentially expressed genes were mainly involved in leukocyte differentiation, chemokine secretion, and immune system regulation. In the meantime, gene set enrichment analysis (GSEA) showed that immune-related signaling pathways, such as transforming growth factor beta (TGF-β) signaling and tumor necrosis factor alpha (TNF-α)/nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling, were enriched in NSN, while cell proliferation–related signaling pathways were enriched in SN, including MYC signaling and G2M checkpoint signaling. We further identified SIGLEC15 as a top upregulated gene in SN. However, RNAscope assay showed that SIGLEC15 was not largely co-expressed with M2 macrophage marker CD163. We then selected eight pairs of lymph nodes for further cytological studies. Flow cytometry analysis revealed that Siglec-15 was expressed on all myeloid cell subsets. The relative expression of SEGLEC15 (SN/NSN) was correlated with the microsatellite instability (MSI) status in colorectal cancer patients. Further studies found that small interfering ribonucleic acid (siRNA)-mediated silencing of SLGLEC15 can enhance the anti-tumor function of T cells, as indicated by cytokine release analysis. In conclusion, we presented here a first report on the gene expression profiling of the pre-metastatic lymph node in colorectal cancer. The findings in this study suggest that SIGLEC15 plays an important role in SN immunosuppression. SEGLEC15 silencing could be a therapeutic strategy for restoring T cell function in tumor SNs.

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

Cancer Cell International ◽

10.1186/s12935-021-02058-9 ◽

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.

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