Downregulation of S100 Calcium Binding Protein A9 in Esophageal Squamous Cell Carcinoma

Pawar, Harsh; Srikanth, Srinivas M.; Kashyap, Manoj Kumar; Sathe, Gajanan; Chavan, Sandip; Singal, Mukul; Manju, H. C.; Kumar, K.V. Veerendra; Vijayakumar, M.; Sirdeshmukh, Ravi; Pandey, Akhilesh; Prasad, T. S. Keshava; Gowda, Harsha; Kumar, Rekha V.

doi:10.1155/2015/325721

Cited by 9 publications

(4 citation statements)

References 41 publications

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“…Based on the reference map of HCA, we found many conventional immune cell markers are expressed in nonimmune cell types. For example, conventional monocyte marker S100A9 was expressed in esophageal squamous epithelium cells (Epithelial cell_4) (Supplementary Figure 9), which was confirmed by previous studies [25,26]. Canonical HSC marker SPINK2 was expressed higher in epididymal epithelial cells (Epithelial cell_7) than HSCs (Stem cell_1) (Supplementary Figure 9).…”

Section: Discussionsupporting

confidence: 81%

Scalable batch-correction approach for integrating large-scale single-cell transcriptomes

Shen

et al. 2022

Briefings in Bioinformatics

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Integration of accumulative large-scale single-cell transcriptomes requires scalable batch-correction approaches. Here we propose Fugue, a simple and efficient batch-correction method that is scalable for integrating super large-scale single-cell transcriptomes from diverse sources. The core idea of the method is to encode batch information as trainable parameters and add it to single-cell expression profile; subsequently, a contrastive learning approach is used to learn feature representation of the additive expression profile. We demonstrate the scalability of Fugue by integrating all single cells obtained from the Human Cell Atlas. We benchmark Fugue against current state-of-the-art methods and show that Fugue consistently achieves improved performance in terms of data alignment and clustering preservation. Our study will facilitate the integration of single-cell transcriptomes at increasingly large scale.

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Section: Discussionsupporting

confidence: 81%

Scalable batch-correction approach for integrating large-scale single-cell transcriptomes

Shen

et al. 2022

Briefings in Bioinformatics

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“…Another gene belonging to the EDC is S100A9, which was also strongly down-regulated in both EAC and ESCC. In a proteomic approach, S100A9 was found to be strongly down-regulated in ESCC [31] . Interestingly, also the transglutaminase 3, which is responsible for crosslinking EDC matrix proteins was down-regulated.…”

Section: Resultsmentioning

confidence: 99%

Genome-Wide Analysis of Barrett's Adenocarcinoma. A First Step Towards Identifying Patients at Risk and Developing Therapeutic Paths

Dai

Wang

González-López

et al. 2018

Translational Oncology

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BACKGROUND: Barrett's esophagus metaplasia is the key precursor lesion of esophageal adenocarcinoma. The aim of this study was to find a subset of markers that may allow the identification of patients at risk for esophageal adenocarcinoma, and to determine genes differentially expressed in esophageal squamous cell carcinoma. METHODS: Laser capture microdissection technique was applied to procure cells from defined regions. Genome-wide RNA profiling was performed on esophageal adenocarcinoma (n = 21), Barrett's esophagus (n = 20), esophageal squamous carcinoma (n = 9) and healthy esophageal biopsies (n = 18) using the Affymetrix Human Genome U133plus 2.0 array. Microarray results were validated by quantitative real-time polymerase chain reaction in a second and independent cohort and by immunohistochemistry of two putative markers in a third independent cohort. RESULTS: Through unsupervised hierarchical clustering and principal component analysis, samples were separated into four distinct groups that match perfectly with histology. Many genes down-regulated in esophageal cancers belong to the epidermal differentiation complex or the related GO-group “cornified envelope” of terminally differentiated keratinocytes. Similarly, retinol metabolism was strongly down-regulated. Genes showing strong overexpression in esophageal carcinomas belong to the GO groups extracellular region /matrix such as MMP1, CTHRC1, and INHBA. According to an analysis of genes strongly up-regulated in both esophageal adenocarcinoma and Barrett's esophagus, REG4 might be of particular interest as an early marker for esophageal adenocarcinoma. CONCLUSIONS: Our study provides high quality data, which could serve for identification of potential biomarkers of Barrett's esophagus at risk of esophageal adenocarcinoma progression.

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“…Specifically, calcium supplementation in PO markedly changed bone mineral and organic matrix quality (28). In addition, S100A9 expressed earlier than the appearance of neutrophilics in the airway of neutrophilic inflammation, and directly activated inflammasome in the airway in asthma (29,30). Due to its expression in inflammation, S100A9 had been indicated to play a significant role in cell proliferation (31).…”

Section: Discussionmentioning

confidence: 99%

Hub genes and gene functions associated with postmenopausal osteoporosis predicted by an integrated method

et al. 2018

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Postmenopausal osteoporosis (PO) imposes great burden on individuals and society. This study predicted hub genes and gene functions for PO by an integration of the convergent evidence (CE) method, rank product (RP) algorithm and the combing of P-values. Using the gene expression data, genes were ranked by the CE method, RP algorithm and combing P-values, respectively. Subsequently, the top 100 genes were selected from each of the three gene lists, and then the common genes for two or three methods were denoted as informative genes of PO. A mutual information network (MIN) was constructed for the informative genes utilizing the context likelihood of relatedness algorithm. Topological centrality (degree) analysis was conducted on the MIN to investigate hub genes. Then we performed Gene Ontology (GO) enrichment analysis dependent upon the Biological Networks Gene Ontology tool (BiNGO) plugin of Cytoscape to investigate hub gene functions for PO patients. Consequently, a total of 82 informative genes were obtained by integrating the results of the three methods. There were 82 nodes and 1,741 edges in the MIN, of which 8 hub genes were identified, such as PFN1, EEF2 and S100A9. The result of GO enrichment analysis showed that 49 GO terms with P<0.001 were detected, especially the top 5 gene sets were defined as hub gene functions of PO, for instance, translational elongation, translation and cellular macromolecule biosynthetic process. In conclusion, we have predicted 8 hub genes and 5 hub gene functions associated with PO patients. The findings might help understand the molecular mechanism underlying PO.

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Downregulation of S100 Calcium Binding Protein A9 in Esophageal Squamous Cell Carcinoma

Cited by 9 publications

References 41 publications

Scalable batch-correction approach for integrating large-scale single-cell transcriptomes

Scalable batch-correction approach for integrating large-scale single-cell transcriptomes

Genome-Wide Analysis of Barrett's Adenocarcinoma. A First Step Towards Identifying Patients at Risk and Developing Therapeutic Paths

Hub genes and gene functions associated with postmenopausal osteoporosis predicted by an integrated method

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