Revealing novel biomarkers for oesophageal squamous cell carcinoma through integrated single-cell RNA sequencing analysis

This study employs single-cell RNA sequencing (scRNA-seq) to analyse oesophageal squamous cell carcinoma (ESCC), identifying 10 potential biomarkers (ALDH2, ANGPT2, APPL1, ARPC2, CAD, CALM1, CLDN7, CLTB, F2RL3, LPAR1) associated with radiation exposure. Methodology involves scRNA-seq for data partitioning, pre-processing, clustering, and differential expression analysis. Dysregulated genes are identified through comprehensive gene ontology (GO) annotations, and ESCC-related pathways are explored via the Kyoto encyclopedia of genes and genomes (KEGG) database. Analysis of 38 genes reveals distinct patterns under radiation exposure, enriching understanding of ESCC-related processes, components, and functions. This research provides a holistic view of ESCC's molecular landscape, emphasising the clinical significance of identified biomarkers and contributing significantly to the understanding of this complex malignancy.

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Publication Details

Journal
International Journal of Data Mining and Bioinformatics
Published
2026-01-01
DOI
https://doi.org/10.1504/ijdmb.2026.150963
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00
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article

Revealing novel biomarkers for oesophageal squamous cell carcinoma through integrated single-cell RNA sequencing analysis

Manash Pratim Dutta, Dhruba K. Bhattacharyya, Bikash Kumar Baruah, Subhasish Banerjee
International Journal of Data Mining and Bioinformatics
Single-cell and spatial transcriptomics
article

Revealing novel biomarkers for oesophageal squamous cell carcinoma through integrated single-cell RNA sequencing analysis

Manash Pratim Dutta, Dhruba K. Bhattacharyya, Bikash Kumar Baruah, Subhasish Banerjee
article en

Abstract

This study employs single-cell RNA sequencing (scRNA-seq) to analyse oesophageal squamous cell carcinoma (ESCC), identifying 10 potential biomarkers (ALDH2, ANGPT2, APPL1, ARPC2, CAD, CALM1, CLDN7, CLTB, F2RL3, LPAR1) associated with radiation exposure. Methodology involves scRNA-seq for data partitioning, pre-processing, clustering, and differential expression analysis. Dysregulated genes are identified through comprehensive gene ontology (GO) annotations, and ESCC-related pathways are explored via the Kyoto encyclopedia of genes and genomes (KEGG) database. Analysis of 38 genes reveals distinct patterns under radiation exposure, enriching understanding of ESCC-related processes, components, and functions. This research provides a holistic view of ESCC's molecular landscape, emphasising the clinical significance of identified biomarkers and contributing significantly to the understanding of this complex malignancy.

International Journal of Data Mining and BioinformaticsVol. 30(1/2)
Tezpur University (IN), Cotton University (IN), National Institute of Technology Arunachal Pradesh (IN)
Openalex Percentile: Top 96%
Single-cell and spatial transcriptomics
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