PhD Scientific Days 2026

Pathological and Oncological Sciences 1.

Microbiome-Derived Biomarkers Predict Response to Immune Checkpoint Inhibitors in Urologic Malignancies

Előadó neve

Dr. Magyar, Balázs

Neptune code

HOSD6M

Előadó munkahelye

Semmelweis University, Department of Urology

Előadó telefonszáma

+36205919661

Előadó e-mail címe

sonatrax@gmial.com

Az előadás címe

Microbiome-Derived Biomarkers Predict Response to Immune Checkpoint Inhibitors in Urologic Malignancies

Szerző(k) neve és munkahelye

Magyar Balázs¹, Juhász János², Hermann-Váradi Melinda¹, Horváth Orsolya³, Soós Edina³, Korda Sára¹, Szűcs Miklós¹, Nyirády Péter¹, Szarvas Tibor⁴

1: Department of Urology, Semmelweis University, Budapest
2: Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest
3: Department of Uro-Oncology and Pharmacology, National Institute of Oncology, Budapest
4: Department of Urology, University of Duisburg-Essen, Essen

Bemutatás módja

Szóbeli

Szekció

Pathological and Oncological Sciences 1.

Language of the presentation

English

Preferred session

Pathological and Oncological Sciences

Összefoglaló szövege

Introduction
Immune checkpoint blockade (ICB) has improved outcomes in urothelial and renal cell carcinoma (UC, RCC), yet response rates remain heterogeneous. It is well established that the gastrointestinal microbiome plays a pivotal role in the maturation and modulation of our immune system. The role of the gut microbiome in modulating immune checkpoint inhibitor (ICI) efficacy has recently become a topic of intensive research.

Aims
To profile the stool microbiome of patients with UC and RCC treated with ICIs using integrated taxonomic and metabolic pathway (MP) analyses to identify relevant microbiome-related pathways and predictive markers.

Method
Pre-treatment fecal samples from 19 UC and 11 RCC patients treated with ICIs were analyzed by shotgun metagenomic sequencing followed by taxonomic and functional profiling. LEfSe analysis identified the best predictive taxa and MPs across endpoints. Associations between microbial taxa, metabolic pathways, and clinical outcomes—including overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and disease control rate (DCR)—were examined using a custom scoring system. Correlations between pre-ICI medications and outcomes were also explored.

Results
Taxon-level LEfSe combined with our scoring system identified Bacteroides stercoris and the genera Blautia and Butyricimonas as the strongest negative predictors. MP-level LEfSe revealed five pathways linked to multiple endpoints, including arginine, sucrose, and dTDP-β-D-fucofuranose metabolism. Integrating key contributing species (Akkermansia muciniphila, Bacteroides stercoris, Ruminococcus lactaris) yielded a composite biomarker strongly correlating with all endpoints. ROC analysis showed AUCs of 0.824 (10-month OS), 0.737 (PFS), 0.856 (DCR), and 0.988 (ORR). Pre-therapy antibiotic use, especially within three months, was associated with worse outcomes.

Conclusion
This study identifies key microbial biomarkers associated with clinical outcomes in UC and RCC patients treated with ICIs. It confirms the role of Akkermansia muciniphila and highlights novel candidates, including Bacteroides stercoris and a three-taxon composite marker with strong predictive value.

Funding
Supported by the Hungarian Ministry of Culture and Innovation and the National Research, Development and Innovation Fund (K139059).

University

Semmelweis University

Supervisor

Prof. Dr. Szarvas Tibor

Publication of my abstract

I do not give consent to the publication of my abstract on the website of the congress.

phd.section.field

in doctoral studies before complex exam (PhD)

Kind

Szabad

Status

elfogadva

Accepted presentation method

szóbeli

Előadás fájl jóváhagyás

nem rendelkezett róla

Előadó

9787

Start

15:15

End

15:25