PhD Scientific Days 2024

Budapest, 9-10 July 2024

Poster Session Q - Pathological and Oncological Sciences 2.

Characteristic metabolic differences of tumour patients influence the subpopulation distribution of T cell


Viktória Varga1, Dániel Sztankovics1, Dorottya Moldvai1, Daniella Kumanovszki2, Gábor Barna1, Anna Sebestyén1
1: Department of Pathology and Experimental Cancer Research, Semmelweis University, Budapest, Hungary
2: Department os Dermatology, Venerology, and DErmatooncology, Semmelweis Uviversity, Budapest, Hungary

Text of the abstract

There are several data about the importance of heterogeneity in patients’ metabolic characteristics (eg. diabetes mellitus, lipid metabolism disorders). These can influence the therapeutic response and side effects with special importance regarding to recently developing immunotherapy. In our study the distribution of different lymphocyte populations and the metabolic heterogeneity of diagnostic tissues were analysed in cancer patients.
Special clinical cohorts were selected in archived melanoma tissue collection to analyse mTOR activity, glucose and lipid metabolism markers and their heterogeneity using tissue microarray – immunohistochemtry (p-mTOR, p-S6, p-ser473 Akt, Rictor, Glut1, HK2, FASN, CPT1a, etc). Additionally, in a new prospective study, peripheral blood sample collections have been started to build and analyse different lymphocyte populations of patients by flowcytometry ((established markers CD3, CD4, CD8, KLRG, PD1, CD56, CD16, etc.).
Multi-parametric (see above) and multi-colour (FITC, PE, PC5, AFP, AF750, etc.) flow cytometry analyses were established in our research group testing several different antibodies (n=15) from different companies to minimalize sample size and reagent needs. Based on the first tested clinical melanoma and control samples, we can distinguish exhausted, senescent and lipid receptor expressing T and NK cell populations in small sample size. Elderly and hyperlypidemic controls shows some similarity in lipid transporter molecule profiles of T lymphocytes, however, the flow cytometry results showed individual differences in melanoma cases. To perform immunohistochemistry several tissue blocks were collected preparing melanoma malignum TMA. Additionally, immunohistochemistry stainings were also established.
The obtained ethical permission allowed to start large patient’s collections. Additionally, the established methods and our preliminary results will help to perform the main study. Our final goal is to compare clinical data (including metabolic characteristic of patients, treatment response, survival), immune-senescence cell distributions and metabolic tissue heterogeneity in immune-checkpoint inhibitor treated melanoma cases.
Supported by: TKP2021-EGA-24, NKFI-K-142799, EFOP-3.6.3-VEKOP-16-2017-00009.