PhD Scientific Days 2025

Poster Session II. - E: Pathological and Oncological Sciences

Large-scale integrative analysis reveals mutational signatures and their prognostic impact in breast cancer

Előadó neve

Dr. Posta Máté

Neptun code

DP77CG

Előadó munkahelye

Institute of Molecular Life Sciences, HUN-REN Research Centre for Natural Sciences, Budapest, Hungary; Department of Bioinformatics, Semmelweis University, Budapest, Hungary

Előadó telefonszáma

+36209925764

Előadó e-mail címe

posta.mate@gmail.com

Az előadás címe

Large-scale integrative analysis reveals mutational signatures and their prognostic impact in breast cancer

Szerző(k) neve és munkahelye

Máté Posta¹, Balázs Győrffy²

1: Institute of Molecular Life Sciences, HUN-REN Research Centre for Natural Sciences, Budapest, Hungary; Department of Bioinformatics, Semmelweis University, Budapest, Hungary
2: Institute of Molecular Life Sciences, HUN-REN Research Centre for Natural Sciences, Budapest, Hungary; Department of Bioinformatics, Semmelweis University, Budapest, Hungary; Department of Biophysics, Medical School, University of Pecs, Pecs, Hungary

Bemutatás módja

Poszter

Szekció

Poster Session II. - E: Pathological and Oncological Sciences

Language of the presentation

Hungarian

Preferred session

Pathological and Oncological Sciences

Összefoglaló szövege

Introduction: Advancing breast cancer treatment requires a deep understanding of the genetic and molecular mechanisms underlying disease progression. In this study, we investigated pathway-level mutational patterns to reveal molecular interactions that may influence survival outcomes.
Methods: We analyzed mutation data from three major breast cancer cohorts, encompassing 4,586 samples and over 25,000 genes. Focusing on disruptive mutations, we conducted survival analysis using Cox proportional hazards regression to identify associations between gene alterations, pathway disruptions, and patient outcomes.
Results: Our results revealed 17 genes significantly linked to relapse-free survival. Among these, TP53 (HR: 2.04, p = 4.65×10⁻³³), CARD11 (HR: 2.59, p = 1.54×10⁻⁵), and PIK3R1 (HR: 2.27, p = 3.66×10⁻⁵) had the strongest impact. At the pathway level, the most significant KEGG pathways were MicroRNAs in cancer (hsa05206, HR: 2.48, p = 2.69×10⁻³²), Hepatocellular carcinoma (hsa05225, HR: 2.39, p = 8.88×10⁻³⁰), and Breast cancer (hsa05224, HR: 2.38, p = 1.78×10⁻²⁸).
We also observed distinct patterns of mutual exclusivity and co-mutation among gene pairs. Notably, GATA3–TP53 (OR: 0.201, p = 1.42×10⁻³⁷), CDH1–TP53 (OR: 0.336, p = 3.66×10⁻²¹), and AKT1–PIK3CA (OR: 0.199, p = 4.97×10⁻¹³) were mutually exclusive, whereas MAP3K1–PIK3CA (OR: 2.83, p = 4.62×10⁻²³), CBFB–GATA3 (OR: 4.67, p = 3.37×10⁻¹⁸), and AHNAK2–MUC16 (OR: 3.39, p = 1.35×10⁻¹⁵) showed significant co-mutation.
To support future validation studies, we developed an online platform accessible at server2.kmplot.com/breast, enabling researchers to explore pathway-specific findings.
Conclusion: In conclusion, our large-scale integrative analysis identified key mutational patterns associated with relapse-free survival, offering valuable insights to inform future research and therapeutic strategies in breast cancer.
Funding: This project was supported by National Research, Development and Innovation Office (PharmaLab, RRF-2.3.1-21-2022-00015); the 2024-2-1-1-EKÖP-2024-00004 university research scholarship programme of the Ministryfor Culture and Innovation from the source of the National Research, Development and Innovation Fund.

University

Semmelweis University

Supervisor

Prof. Dr. Balázs Győrffy

Publication of my abstract

I give consent to the publication of my abstract on the website of the congress.

Kind

Szabad

Status

elfogadva

Accepted presentation method

poszter

Előadás fájl jóváhagyás

nem rendelkezett róla

Előadó

8069

Start

19:00

End

19:06