진학프로석·박사 채용 접수 플랫폼

We are looking for a post-doctoral researcher to work in the International Centre for Cancer Vaccine Science (ICCVS) hosted by the University of Gdańsk.

The position is offered in the frame of the project No. 2024/ABM/03/KPO/KPOD.07.07-IW.07-0096/24 entitled: “NSCLC Diagnostics - Algoritm (DiaNA)". The project is funded by the Agency for Medical Research in the frame of the National Recovery and Resilience Plan Component D Efficiency, accessibility, and quality of the healthcare system Investment D3.1.1. Complex development of research in medical science and healthcare.

About us

The International Centre for Cancer Vaccine Science (ICCVS) has been established in 2017 as a joint unit of the University of Gdańsk (UG) and the University of Edinburgh (UoE) within a project carried out within the International Research Agendas Programme of the Foundation for Polish Science funded from the European Regional Development Fund. The aim of ICCVS has been comprehensive research into development of novel diagnostic and prognostic markers and personalized anti-cancer therapies and vaccines, followed by their commercialization and implementation into clinical practice. ICCVS works on a range of national and international research projects concentrating on cancer biology and novel approaches to immunotherapies. The focus of the ICCVS is the development of personalized vaccine against non-small cell lung cancer (NSCLC). The approach is based on use of cancer specific T cells that are selected by the special algorithm elaborated at ICCVS. The first in vitro and in vivo studies are very encouraging, and the team plans to start clinical trials in a few years perspective.

More information at: www.iccvs.ug.edu.pl

About the DiaNA project

The DiaNA project aims at elaboration and validation of new diagnostics methods for NSCLC characterized by high accessibility and effectiveness in early detection of the tumour. 

Lung cancer is the most common cause of death of cancer patients of both genders, while non-small cell lung cancer (NSCLC) accounts for 85% of its cases. NSCLC is a serious problem for the health care system, as the high risk group accounts for 3 million individuals, for whom optimal screening diagnostics is still missing. Currently used for this purpose low-dose computer tomography (CT) is characterized by a high false positive rate and low efficiency in diagnostic of small (<1cm) pulmonary nodules and limited availability. Therefore, the goal of the DiaNA project is to provide two new diagnostic methods for NSCLC that will enable efficient populational screening of NSCLC. The methods which have been developing by ICCVS team use only a blood sample and simplify the data analysis using machine learning techniques to enable result interpretation without involving specialized medical personnel.

The ICCVS team has developed two methods for identification of the patients with early-stage NSCLC based on blood tests. Preliminary data indicate high specificity of the identified markers and the diagnostic algorithm. The DiaNA project has been designed to validate the discovered markers in a study involving more than 2 000 cancer patients and high risk healthy individuals.

The first of the two elaborated methods is based on blood sample analysis with flow cytometry. The flow cytometer is currently a standard equipment in laboratories of clinical immunology. Its availability is not a limiting factor for the method implementation. We have established a panel of 16 antibodies to characterize selected populations of natural killer (NK) cells. NK cells are known for their anticancer activity. In parallel, we have developed an analytical algorithm that converts the complex flow cytometry data to a graphical pattern. This way the result interpretation requires only applying the template to the graphical pattern and assessing whether the template and graphical pattern overlaps. Therefore, the procedure takes less than one minute and does not require specialized knowledge.

The studied material for the second elaborated method is also blood. However, this time the blood is analyzed with mass spectrometry. In our previous studies, we identified approximately 7 000 peptides presented by MHC class I molecules of NSCLC, but not by the healthy lung cells of the same donors (these peptides are called neoantigens). Then we observed that 4 of them were also present in the blood of NSCLC patients. Interestingly, we detected them in all tested patient blood samples, but never in samples derived from healthy individuals. The DiaNA project will enable us to validate the diagnostic value of the discovered neoantigens and simplification of the method to make it quick and widely available.

The methods planned for development in the project have a high potential for implementation and commercialization.