ArticleFrontiers in oncology2022
Identification of lymph node metastasis-related genes and patterns of immune infiltration in colon adenocarcinoma.
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed, 1 citations in OpenAlex.
- Single-cell transcriptome analysis profiling lymphatic invasion-related TME in colorectal cancer.Scientific reports · 2024Article
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Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Backgrounds: Colon adenocarcinoma(COAD) is one of the most common tumors of the digestive tract. Lymph node metastasis (LNM) is a well-established prognostic factor for COAD. The mechanism of COAD lymph node metastasis in immunology remains unknown. The identification of LNM-related biomarkers of COAD could help in its treatment. Thus, the current study was aimed to identify key genes and construct a prognostic signature. Methods: Gene expression and clinical data were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes were calculated by using R software. GO functional and KEGG pathway enrichment analysis were processed. The CIBERSORT algorithm was used to assess immune cell infiltration. STRING database was used to screen key genes and constructed a protein-protein interaction network (PPI network). The LASSO-Cox regression analysis was performed based on the components of the PPI network. The correlation analysis between LNM-related signature and immune infiltrating cells was then investigated. TISIDB was used to explore the correlation between the abundance of immunomodulators and the expression of the inquired gene. Results: In total, 394 differentially expressed genes were identified. After constructing and analyzing the PPI network, 180 genes were entered into the LASSO-Cox regression model, constructing a gene signature. Five genes(PMCH, LRP2, NAT1, NKAIN4, and CD1B) were identified as LNM-related genes of clinical value. Correlation analysis revealed that LRP2 and T follicular helper cells (R=0.34, P=0.0019) and NKAIN4 and T follicular helper cells (R=0.23, P=0.041) had significant correlations. Immunologic analysis revealed that LRP2 and NKAIN4 are potential coregulators of immune checkpoints in COAD. Conclusion: In general, this study revealed the key genes related to lymph node metastasis and prognostic signature. Several potential mechanisms and therapeutic and prognostic targets of lymph node metastasis were also demonstrated in COAD.
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