Identification and subsequent validation of transcriptomic signature associated with metabolic status in endometrial cancer

Iwona Sidorkiewicz; Maciej Jóźwik; Angelika Buczyńska; Anna Erol; Marcin Jóźwik; Marcin Moniuszko; Katarzyna Jarząbek; Magdalena Niemira; Adam Krętowski

doi:10.1038/s41598-023-40994-w

Identification and subsequent validation of transcriptomic signature associated with metabolic status in endometrial cancer

Sci Rep. 2023 Aug 23;13(1):13763. doi: 10.1038/s41598-023-40994-w.

Authors

Affiliations

¹ Clinical Research Centre, Medical University of Białystok, Marii Skłodowskiej-Curie 24a, 15-276, Białystok, Poland. iwona.sidorkiewicz@umb.edu.pl.
² Department of Gynecology and Gynecologic Oncology, Medical University of Białystok, 15-276, Białystok, Poland.
³ Clinical Research Centre, Medical University of Białystok, Marii Skłodowskiej-Curie 24a, 15-276, Białystok, Poland.
⁴ Department of Gynecology and Obstetrics, Collegium Medicum, University of Warmia and Mazury in Olsztyn, 10-045, Olsztyn, Poland.
⁵ Department of Regenerative Medicine and Immune Regulation, Medical University of Bialystok, 15-269, Białystok, Poland.
⁶ Department of Allergology and Internal Medicine, Medical University of Bialystok, 15-276, Białystok, Poland.
⁷ Laboratory of Genetic and Molecular Diagnostics, Maria Skłodowska-Curie Białystok Oncology Center, 15-027, Białystok, Poland.
⁸ Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Białystok, 15-276, Białystok, Poland.

Abstract

Aberrant metabolism has been identified as a main driver of cancer. Profiling of metabolism-related pathways in cancer furthers the understanding of tumor plasticity and identification of potential metabolic vulnerabilities. In this prospective controlled study, we established transcriptomic profiles of metabolism-related pathways in endometrial cancer (EC) using a novel method, NanoString nCounter Technology. Fifty-seven ECs and 30 normal endometrial specimens were studied using the NanoString Metabolic Panel, further validated by qRT-PCR with a very high similarity. Statistical analyses were by GraphPad PRISM and Weka software. The analysis identified 11 deregulated genes (FDR ≤ 0.05; |FC|≥ 1.5) in EC: SLC7A11; SLC7A5; RUNX1; LAMA4; COL6A3; PDK1; CCNA1; ENO1; PKM; NR2F1; and NAALAD2. Gene ontology showed direct association of these genes with 'central carbon metabolism (CCM) in cancer'. Thus, 'CCM in cancer' appears to create one of the main metabolic axes in EC. Further, transcriptomic data were functionally validated with drug repurposing on three EC cell lines, with several drug candidates suggested. These results lay the foundation for personalized therapeutic strategies in this cancer. Metabolic plasticity represents a promising diagnostic and therapeutic option in EC.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Carbon
Endometrial Neoplasms* / genetics
Female
Gene Expression Profiling
Genes, cdc
Humans
Prospective Studies
Transcriptome*

Substances

Carbon