IVANA KURELAC

Associate Professor

University of Bologna

Italy

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Dr. Ivana Kurelac is an Associate Professor at the University of Bologna, Italy. Her research primarily focuses on ovarian cancer, highlighting advancements in detection methods and treatment responses through innovative techniques such as AI-aided holographic flow cytometry and liquid biopsy. Additionally, she explores mitochondrial DNA variants in relation to various cancers, including pancreatic cancer and neuroblastoma. Dr. Kurelac's contributions aim to enhance understanding of cancer biology and improve therapeutic strategies.

Articles (10)

Year:

2025

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2025

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2024

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2024

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2024

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2023

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2023

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2023

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2022

Year:

2022

Collaborators (9)

Pietro Alifano

Full professor of Microbiology

University of Salerno

ITALY

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Alessandro SALVI

Prof.

University of Brescia

ITALY

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Francesca Borrelli

Istituto di Scienze Applicate e Sistemi Intelligenti "Eduardo Caianiello"

ITALY

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Giulia Girolimetti

Università del Salento

ITALY

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Jaromír Běhal

Palacký University

CZECH REPUBLIC

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Leonardo Henry Eusebi

Associate Professor of Gastroenterology

University of Bologna

ITALY

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Flora Guerra

Associate Professor

University of Salerno

ITALY

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Mario Capasso

Associate Professor

Università degli Studi di Napoli Federico II

ITALY

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Massimiliano Maria VILLONE

Associate Professor

University of Naples Federico II

ITALY

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IVANA KURELAC

Research Interests

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Articles (10)

Immunomagnetic enrichment coupled to PAX8/TP53 molecular pathology approach increases sensitivity in the detection of ovarian cancer cells in ascites.

Mitochondrial chaperonin DNAJC15 promotes vulnerability to ferroptosis of chemoresistant ovarian cancer cells.

Dysregulation of a Subset of Circulating and Vesicle-Associated miRNA in Pancreatic Cancer

Pathogenic mitochondrial DNA variants are associated with response to anti-VEGF therapy in ovarian cancer PDX models.

The landscape of rare mitochondrial DNA variants in sudden cardiac death: A potential role for ATP synthase.

AI-aided holographic flow cytometry for label-free identification of ovarian cancer cells in the presence of unbalanced datasets

Label-free liquid biopsy through the identification of tumor cells by machine learning-powered tomographic phase imaging flow cytometry

Phenotyping neuroblastoma cells through intelligent scrutiny of stain-free biomarkers in holographic flow cytometry.

NDUFS3 knockout cancer cells and molecular docking reveal specificity and mode of action of anti-cancer respiratory complex I inhibitors.

Finding intracellular lipid droplets from the single-cell biolens' signature in a holographic flow-cytometry assay.

Collaborators (9)

Pietro Alifano

Alessandro SALVI

Francesca Borrelli

Giulia Girolimetti

Jaromír Běhal

Leonardo Henry Eusebi

Flora Guerra

Mario Capasso

Massimiliano Maria VILLONE

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