lncRNA EGOT across cancers: TCGA analysis

Introduction long-non-coding RNAs (lncRNAs) are important new players in the epigenetic control of cellular phenotypes. One of the lncRNAs is the eosinophil granule ontogeny transcript (EGOT), in which changes in expression levels are correlated with pathological conditions, including tumorigenesis and viral infections. In spite of many studies, the biological role and diagnostics utility of EGOT remains unclear. Material and methods EGOT was analyzed based on the TCGA, including pathological and clinical features, cellular pathways, and genomic and cellular changes. Results We observed an association of higher EGOT expression with better survival in breast invasive carcinoma (BRCA), head and neck squamous cell carcinoma (HNSC), kidney renal clear cell carcinoma (KIRC) and worse patients' survival for liver hepatocellular carcinoma (LIHC). Expression levels of EGOT differ in the case of HNSC, KIRC and LIHC. Critical cellular pathways and processes are changed depending on the EGOT. Moreover, immune profile, cancer subtypes, and differences in the proliferation, wound healing ability, stromal fraction, and intratumor heterogeneity depending on these lncRNA levels were noticed and differ mostly for BRCA and KIRC. Conclusions EGOT seems to be a potential prognostic biomarker in clinical use. One of the possibilities that connected all of the analyzed types of cancers and changes in EGOT expression is viral activity and immunological response to viral infection.

Authors

Institutions

Publication Details

Journal
Archives of Medical Science
Published
2025-08-18
DOI
https://doi.org/10.5114/aoms/205791
Primary Topic
Cancer-related molecular mechanisms research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

lncRNA EGOT across cancers: TCGA analysis

Joanna Kaźmierska, Ewa Leporowska, Anna Przybyła, Kacper Guglas et al.
Archives of Medical Science
Cancer-related molecular mechanisms research
article

lncRNA EGOT across cancers: TCGA analysis

Joanna Kaźmierska, Ewa Leporowska, Anna Przybyła, Kacper Guglas, Patrycja Mantaj, Zefiryn Cybulski, Piotr Białas, Anna Florczak, Marlena Janiczek-Polewska, Paulina Poter, Joanna Kozłowska-Masłoń, Tomasz Kolenda, Anna Malicka-Durczak, Małgorzata Nowak, Anna Zapłata, Dominika Połczyńska-Hałas
article en

Abstract

Introduction long-non-coding RNAs (lncRNAs) are important new players in the epigenetic control of cellular phenotypes. One of the lncRNAs is the eosinophil granule ontogeny transcript (EGOT), in which changes in expression levels are correlated with pathological conditions, including tumorigenesis and viral infections. In spite of many studies, the biological role and diagnostics utility of EGOT remains unclear. Material and methods EGOT was analyzed based on the TCGA, including pathological and clinical features, cellular pathways, and genomic and cellular changes. Results We observed an association of higher EGOT expression with better survival in breast invasive carcinoma (BRCA), head and neck squamous cell carcinoma (HNSC), kidney renal clear cell carcinoma (KIRC) and worse patients' survival for liver hepatocellular carcinoma (LIHC). Expression levels of EGOT differ in the case of HNSC, KIRC and LIHC. Critical cellular pathways and processes are changed depending on the EGOT. Moreover, immune profile, cancer subtypes, and differences in the proliferation, wound healing ability, stromal fraction, and intratumor heterogeneity depending on these lncRNA levels were noticed and differ mostly for BRCA and KIRC. Conclusions EGOT seems to be a potential prognostic biomarker in clinical use. One of the possibilities that connected all of the analyzed types of cancers and changes in EGOT expression is viral activity and immunological response to viral infection.

Archives of Medical Science
Poznan University of Medical Sciences (PL), Greater Poland Cancer Center (PL)
Openalex Percentile: Top 73%
Cancer-related molecular mechanisms research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.