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Decreased gene expression of antiangiogenic factors in endometrial cancer : qPCR analysis and machine learning modelling
ID
Roškar, Luka
(
Author
),
ID
Kokol, Marko
(
Author
),
ID
Pavlič, Renata
(
Author
),
ID
Roškar, Irena
(
Author
),
ID
Smrkolj, Špela
(
Author
),
ID
Lanišnik-Rižner, Tea
(
Author
)
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MD5: 5C3BE213D66798F8B2C7C71FBFF85775
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https://www.mdpi.com/2072-6694/15/14/3661
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Abstract
Endometrial cancer (EC) is an increasing health concern, with its growth driven by an angiogenic switch that occurs early in cancer development. Our study used publicly available datasets to examine the expression of angiogenesis-related genes and proteins in EC tissues, and compared them with adjacent control tissues. We identified nine genes with significant differential expression and selected six additional antiangiogenic genes from prior research for validation on EC tissue in a cohort of 36 EC patients. Using machine learning, we built a prognostic model for EC, combining our data with The Cancer Genome Atlas (TCGA). Our results revealed a significant up-regulation of IL8 and LEP and down-regulation of eleven other genes in EC tissues. These genes showed differential expression in the early stages and lower grades of EC, and in patients without deep myometrial or lymphovascular invasion. Gene co-expressions were stronger in EC tissues, particularly those with lymphovascular invasion. We also found more extensive angiogenesis-related gene involvement in postmenopausal women. In conclusion, our findings suggest that angiogenesis in EC is predominantly driven by decreased antiangiogenic factor expression, particularly in EC with less favourable prognostic features. Our machine learning model effectively stratified EC based on gene expression, distinguishing between low and high-grade cases.
Language:
English
Keywords:
endometrial cancer
,
angiogenic factor
,
tumour-adjacent tissue
,
machine learning
,
TCGA
,
LEP
Work type:
Article
Typology:
1.01 - Original Scientific Article
Organization:
MF - Faculty of Medicine
Publication status:
Published
Publication version:
Version of Record
Year:
2023
Number of pages:
24 str.
Numbering:
Vol. 15, iss. 14, art. 3661
PID:
20.500.12556/RUL-185543
UDC:
616-006
ISSN on article:
2072-6694
DOI:
10.3390/cancers15143661
COBISS.SI-ID:
159457795
Publication date in RUL:
10.08.2026
Views:
138
Downloads:
60
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Record is a part of a journal
Title:
Cancers
Shortened title:
Cancers
Publisher:
MDPI
ISSN:
2072-6694
COBISS.SI-ID:
517914137
Licences
License:
CC BY 4.0, Creative Commons Attribution 4.0 International
Link:
http://creativecommons.org/licenses/by/4.0/
Description:
This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Secondary language
Language:
Slovenian
Keywords:
rak endometrija
,
angiogeni faktor
,
tkivo ob tumorju
,
strojno učenje
,
TCGA
,
LEP
Projects
Funder:
ARRS - Slovenian Research Agency
Project number:
J3-2535
Name:
Vloga androgenov pri hormonsko odvisnih boleznih: pomen za diagnostiko in zdravljenje
Funder:
University Medical Centre Ljubljana
Project number:
TP 202110160
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