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NSCLC Diagnostics - Algorithm

Shaping the future of lung cancer diagnostics

A next-generation blood analysis approach combining immunology and machine learning

Project

What is DiaNA

The NSCLC Diagnostics – Algorithm (DiaNA) project is a research initiative conducted by the International Centre for Cancer Vaccine Science (ICCVS) at the University of Gdańsk. Its goal is to develop and validate novel blood-based diagnostic methods for non-small cell lung cancer (NSCLC). The project focuses on solutions that are fast, accessible and suitable for large-scale screening, with results that can be interpreted using standardized algorithms.

The implementation of the DiaNA project takes place thanks to the funding from the Medical Research Agency within the framework of the competition for scientific entities to carry out applied research in the biomedical area (2024 ABM/03/KPO) within the National Recovery and Resilience Plan, Component D Efficiency, Accessibility and Quality of the Health System, Investment D3.1.1 Comprehensive development of research in medical and health sciences.

Why it matters

The challenge

Lung cancer remains one of the leading causes of cancer-related mortality worldwide. Non-small cell lung cancer accounts for approximately 85% of all lung cancer cases.

Current diagnostic methods are often limited by accessibility, cost, and a high rate of false-positive results.

Our response

DiaNA addresses these challenges by developing minimally invasive blood-based diagnostic approaches supported by advanced data analysis and machine learning tools.

Our diagnostic approaches

Method 1

Flow cytometry–based diagnostics

Blood samples are analyzed using flow cytometry, a standard clinical technology. A dedicated panel of antibodies enables the characterization of immune cell populations, particularly natural killer (NK) cells. Results are interpreted using a graphical algorithm, allowing rapid assessment without the need for highly specialized personnel.

Method 2

Mass spectrometry–based diagnostics

This approach focuses on identifying cancer-specific peptides (neoantigens) present in blood samples of NSCLC patients. Initial studies indicate the presence of unique peptide signatures detectable only in affected individuals.

Project objectives

Development of innovative blood-based diagnostic methods for NSCLC

Validation of diagnostic accuracy and reproducibility

Integration of machine learning for result interpretation

Improving accessibility of lung cancer screening

News

Stay up to date with the latest developments, milestones and announcements related to the DiaNA project.

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DiaNA Project: From a Blood Sample to Diagnostic Insight 

The NSCLC Diagnostics – Algorithm (DIANA) project, implemented at the International Centre for Cancer Vaccine Science (ICCVS), University of Gdańsk, under the leadership of Prof. Natalia Marek-Trzonkowska, explores whether a single blood sample can provide clinically relevant information for lung cancer diagnostics. The project addresses one of the most pressing challenges in modern oncology. Lung […]

Advancing Early Blood-Based Diagnostics for Non-Small Cell Lung Cancer

Lung cancer remains one of the greatest challenges in modern medicine and is the leading cause of cancer-related deaths among both men and women worldwide. Approximately 85% of all lung cancer cases are classified as non-small cell lung cancer (NSCLC). One of the key reasons for the high mortality associated with this disease is that […]

ABOUT US

About the team

The DiaNA project is carried out at the International Centre for Cancer Vaccine Science (ICCVS), University of Gdańsk — a leading research center focused on innovative cancer diagnostics and immunotherapy.

 

Project leader

Prof. Natalia Marek-Trzonkowska
Project leader, ICCVS University of Gdańsk
Expert in cancer immunology and translational research.

Contact

For media inquiries, collaboration opportunities or general questions regarding the DiaNA project, please contact us.

Coordinator: University of Gdańsk,
International Centre for Cancer Vaccine Science
ul. Kładki 24,
80-822 Gdańsk, Poland
iccvs@ug.edu.pl
iccvs.ug.edu.pl

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