Génexpressziós profil vizsgálata a pajzsmirigy hámeredetű tumoraiban = Gene-expression profiles in the thyroid tumors of epithelial origin

A thyroid tumorok kialakulása az epitelialis carcinogenezis többlépcsős modelljeként irható le. Tumor szuppresszor gének, és az onkogének három fő csoportjába tartozó gének (GTP-kötő protein, sejtmagi transzkripciós faktor, tirozin kináz) mutációinak, expressziós mintázatának megváltozása szerepet játszik a tumor kialakulásában, progressziójában. Célkitűzéseink között szerepelt az irodalomban közölt génexpressziós mintázatok magyarországi populáción való vizsgálata, valamint egyéni rizikóbecslés alátámasztása érdekében egyes gének genetikai polimorfizmusának vizsgálata pajzsmirigy tumoros betegek mintáiból. RNS micro array segítségével meghatározzuk különböző, de főként hámeredetű pajzsmirigy tumorok jellemző génexpressziós profilját, mely megalapozza egy, un: "thyroid chip" megszerkesztését, létrehozását. Eredményeink azt mutatják, hogy meghatározható egy jellegzetes - 90-100 génből álló -génexpressziós profil pajzsmirigy tumorok esetén, de kutatási eredményeink még kvantitatív RT-PCR-os alátámasztásra szorulnak (jelenleg folyó kísérlet), valamint nagyobb mintaszámon vissza kell ellenőrizni hipotézisünket. | Thyroid tumors can be considered as a multi-step model of epithelial carcinogenesis. Tumor-suppressor genes and three classes of oncogenes - coding GPT-binding proteins, nuclear transcription factors and tyrosine kinases - play roles in its development and progression. We aimed to study the pattern of gene expressions in the Hungarian population according to the data in specialized literature, and also analyzing the polymorphism of certain genes from samples of patient with thyroid cancer in the interest of personal risk assessment. We determine the various, but mainly epithelial thyroid tumors' specific profile of gene expression by applying RNA micro array. This might establish the accomplishment of the "thyroid chip". Our results show, that a specific profile of gene expression - consisting of 90-100 genes - is could be determined concerning thyroid tumors, but these results should be supported by using quantitative RT-PCR method (this experiment is currently runs in our institute) in addition our hypothesis is needed to be controlled in wider population

Personalized First-Line Treatment of Metastatic Pancreatic Neuroendocrine Carcinoma Facilitated by Liquid Biopsy and Computational Decision Support

Background: We present the case of a 50-year-old female whose metastatic pancreatic neuroendocrine tumor (pNET) diagnosis was delayed by the COVID-19 pandemic. The patient was in critical condition at the time of diagnosis due to the extensive tumor burden and failing liver functions. The clinical dilemma was to choose between two registered first-line molecularly-targeted agents (MTAs), sunitinib or everolimus, or to use chemotherapy to quickly reduce tumor burden. Methods: Cell-free DNA (cfDNA) from liquid biopsy was analyzed by next generation sequencing (NGS) using a comprehensive 591-gene panel. Next, a computational method, digital drug-assignment (DDA) was deployed for rapid clinical decision support. Results: NGS analysis identified 38 genetic alterations. DDA identified 6 potential drivers, 24 targets, and 79 MTAs. Everolimus was chosen for first-line therapy based on supporting molecular evidence and the highest DDA ranking among therapies registered in this tumor type. The patient’s general condition and liver functions rapidly improved, and CT control revealed partial response in the lymph nodes and stable disease elsewhere. Conclusion: Deployment of precision oncology using liquid biopsy, comprehensive molecular profiling, and DDA make personalized first-line therapy of advanced pNET feasible in clinical settings

Results of viability assays on pancreatic cancer cell lines.

<p>(A) IC₅₀ concentrations of MEK, EGFR and Akt inhibitors measured on MiaPaCa2, BxPC3 and Panc1 cell lines (B) IC₅₀ curves of MEK inhibitor (trametinib), Akt inhibitor (triciribine) and EGFR inhibitor (afatinib) treatment and MEK+Akt (1:1) -/MEK+EGFR (1:1) inhibitor combination therapy on BxPC3 and Panc1 cell lines, curves were generated with GraphPad Prism version 7.00 for Mac (La Jolla, CA, USA) software (C) IC₅₀ concentration of different drug combinations applied in constant ratio (1:1) on BxPC3 and Panc1 cell lines and combination indexes of the same drug combinations calculated with Calcusyn.</p

The in vitro pancreatic cancer cell line model.

<p>This model is based on our protein expression and phosphorylation measurements and viability assays. MiaPaCa2 cell line with KRAS G12C mutation and low EGFR level is highly sensitive to trametinib treatment, combination with other drugs is not necessary and only increases drug toxicity. In case of BxPC3 cell line with wild type KRAS and high EGFR level/phosphorylation the feedback activation of EGFR/PI3K/Akt to trametinib treatment has a great impact, therefore combination of the MEK inhibitor with EGFR or Akt inhibitor both results drug synergism. Panc1 shows resistance to MEK inhibitors and the combination with the EGFR inhibitor afatinib does not decrease its IC₅₀ concentration to an appropriate level. Our model shows, that the presence of G12D mutation (which activates PI3K/Akt pathway) and the high expression of Akt protein both indicate the use of MEK+Akt inhibitor combination.</p

Protein expression and phosphorylation analysis of the used pancreatic cancer cell lines.

<p>(A) EGFR and pY1068 EGRF, Akt and pS473 Akt, ERK1/2 and pT202/Y204 ERK were analyzed with SDS page/Western blot method. (B) The expression and phosphorylation of all proteins were compared to the KRAS wild type cell line, BxPC3. α-tubulin was used as loading control. (Original Western blot images: <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0185687#pone.0185687.s001" target="_blank">S1A and S1B Fig</a>).</p

Response of pancreatic cancer cell lines to trametinib treatment.

<p>Total Akt level and Akt activation status (pS473) were analyzed by Western blot. A representative blot and graphic evaluation of 3 independent experiments. α-tubulin was used as loading control. (Original Western blot image: <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0185687#pone.0185687.s001" target="_blank">S1C Fig</a>).</p