Plakin Expression in Serous Epithelial Ovarian Cancer Has the Potential to Impede Metastatic Spread and Epithelial–Mesenchymal Transition: A Comparative Expression Analysis of Immunohistochemical and In Silico Datasets

Epithelial ovarian cancer is aggressive and causes high mortality among women worldwide. Members of the plakin family are essential to maintain cytoskeletal integrity and key cellular processes. In this study we characterised the expression of plakins, particularly plectin (PLEC), periplakin (PPL), envoplakin (EVPL), and EMT-related proteins by immunohistochemistry in n = 48 patients' samples to evaluate a potential correlation of plakin expression with EMT as EOC progresses. These tissue plakin and EMT expression analyses were further evaluated by in vitro cell line expression and correlated with the expression of these molecules using publicly available datasets such as Cancer Genome Atlas (TCGA) and Clinical Proteome Tumour Analysis Consortium (CPTAC) datasets. We demonstrate that the expression of PPL and PLEC plakins is decreased in high-grade compared to low-grade EOCs with mixed EMT marker protein expression. This is supported by the correlation of high PPL and PLEC expression with an epithelial rather than mesenchymal phenotype. Our data suggest a partial loss of plakin expression as EOC tumours progress. This may impact the connections of plakins with membrane-bound receptors, which impede the downstream signalling required for the initiation of EMT as the tumours progress.

Authors

Institutions

Publication Details

Journal
Cancers
Published
2024-12-06
DOI
https://doi.org/10.3390/cancers16234087
Citations
3
Primary Topic
Ovarian cancer diagnosis and treatment
Type
article
Field-Weighted Citation Impact
1.61

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Plakin Expression in Serous Epithelial Ovarian Cancer Has the Potential to Impede Metastatic Spread and Epithelial–Mesenchymal Transition: A Comparative Expression Analysis of Immunohistochemical and In Silico Datasets

Nuzhat Ahmed, George Kannourakis, Tamsin Wesley, Ruth M. Escalona
3 citations
Cancers
Ovarian cancer diagnosis and treatment
1.61
article

Plakin Expression in Serous Epithelial Ovarian Cancer Has the Potential to Impede Metastatic Spread and Epithelial–Mesenchymal Transition: A Comparative Expression Analysis of Immunohistochemical and In Silico Datasets

Nuzhat Ahmed, George Kannourakis, Tamsin Wesley, Ruth M. Escalona
article en
3 citations

Abstract

Epithelial ovarian cancer is aggressive and causes high mortality among women worldwide. Members of the plakin family are essential to maintain cytoskeletal integrity and key cellular processes. In this study we characterised the expression of plakins, particularly plectin (PLEC), periplakin (PPL), envoplakin (EVPL), and EMT-related proteins by immunohistochemistry in n = 48 patients' samples to evaluate a potential correlation of plakin expression with EMT as EOC progresses. These tissue plakin and EMT expression analyses were further evaluated by in vitro cell line expression and correlated with the expression of these molecules using publicly available datasets such as Cancer Genome Atlas (TCGA) and Clinical Proteome Tumour Analysis Consortium (CPTAC) datasets. We demonstrate that the expression of PPL and PLEC plakins is decreased in high-grade compared to low-grade EOCs with mixed EMT marker protein expression. This is supported by the correlation of high PPL and PLEC expression with an epithelial rather than mesenchymal phenotype. Our data suggest a partial loss of plakin expression as EOC tumours progress. This may impact the connections of plakins with membrane-bound receptors, which impede the downstream signalling required for the initiation of EMT as the tumours progress.

CancersVol. 16(23)
Federation University (AU), The University of Melbourne (AU), Hudson Institute of Medical Research (AU), Monash University (AU)
Cancer Research Institute
Good health and well-being
Openalex Percentile: Top 15%
Ovarian cancer diagnosis and treatment
1.61
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.