Biology subjects

Ujfaludi, Z.

Publications and source records attributed to Ujfaludi, Z..

5 recordsLinked to original sources

bioRxiv2024

Predicting immune checkpoint therapy response in three independent metastatic melanoma cohorts

While Immune checkpoint inhibition (ICI) therapy shows significant efficacy in metastatic melanoma, only about 50% respond, lacking reliable predictive methods. We introduce a panel of six proteins aimed at predicting response to ICI therapy. Evaluating previously reported proteins in two untreated melanoma cohorts, we used a published predictive model (EaSIeR score) to identify potential proteins distinguishing responders and non-responders. Six proteins initially identified in the ICI cohort correlated with predicted response in the untreated cohort. Additionally, three proteins correlated with patient survival, both at the protein, and at the transcript levels, in an independent immunotherapy treated cohort. Our study identifies predictive biomarkers across three melanoma cohorts, suggesting their use in therapeutic decision-making. O_FIG O_LINKSMALLFIG WIDTH=164 HEIGHT=200 SRC="FIGDIR/small/592032v1_ufig1.gif" ALT="Figure 1"> View larger version (63K): org.highwire.dtl.DTLVardef@754668org.highwire.dtl.DTLVardef@1616263org.highwire.dtl.DTLVardef@827009org.highwire.dtl.DTLVardef@1899ba7_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2024

Identifying Ferroptosis Inducers, HDAC, and RTK Inhibitor Sensitivity in Melanoma Subtypes through Unbiased Drug Target Prediction

The utilization of PD1 and CTLA4 inhibitors has revolutionized the treatment of malignant melanoma (MM). However, resistance to targeted and immune-checkpoint-based therapies still poses a significant problem. Here we mine large scale MM proteogenomic data integrating it with MM cell line dependency screen, and drug sensitivity data to identify druggable targets and forecast treatment efficacy and resistance. Leveraging protein profiles from established MM subtypes and molecular structures of 82 cancer treatment drugs, we identified nine candidate hub proteins, mTOR, FYN, PIK3CB, EGFR, MAPK3, MAP4K1, MAP2K1, SRC and AKT1, across five distinct MM subtypes. These proteins serve as potential drug targets applicable to one or multiple MM subtypes. By analyzing transcriptomic data from 48 publicly accessible melanoma cell lines sourced from Achilles and CRISPR dependency screens, we forecasted 162 potentially targetable genes. We also identified genetic resistance in 260 genes across at least one melanoma subtype. In addition, we employed publicly available compound sensitivity data (Cancer Therapeutics Response Portal, CTRPv2) on the cell lines to assess the correlation of compound effectiveness within each subtype. We have identified 20 compounds exhibiting potential drug impact in at least one melanoma subtype. Remarkably, employing this unbiased approach, we have uncovered compounds targeting ferroptosis, that demonstrate a striking 30x fold difference in sensitivity among different subtypes. This implies that the proteogenomic classification of melanoma has the potential to predict sensitivity to ferroptosis compounds. Our results suggest innovative and novel therapeutic strategies by stratifying melanoma samples through proteomic profiling, offering a spectrum of novel therapeutic interventions and prospects for combination therapy. Highlights(1) Proteogenomic subtype classification can define the landscape of genetic dependencies in melanoma (2) Nine proteins from molecular subtypes were identified as potential drug targets for specified MM patients (3) 20 compounds identified that show potential effectiveness in at least one melanoma subtype (4) Proteogenomics can predict specific ferroptosis inducers, HDAC, and RTK Inhibitor sensitivity in melanoma subtypes O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=184 SRC="FIGDIR/small/579424v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@73dd77org.highwire.dtl.DTLVardef@d0cb8eorg.highwire.dtl.DTLVardef@1e4117forg.highwire.dtl.DTLVardef@38b727_HPS_FORMAT_FIGEXP M_FIG Graphical abstract C_FIG

cancer biology↗

bioRxiv2023

Cytoplasmic Aggregation of RPB1 Predicts Failure of Neoadjuvant Chemotherapy

We aimed to investigate the contribution of co-translational protein aggregation to the chemotherapy resistance of tumor cells. Increased co-translational protein aggregation reflects altered translation regulation that may have the potential to buffer transcription under genotoxic stress. As an indicator for such event, we followed cytoplasmic aggregation of RPB1, the aggregation prone largest subunit of RNA polymerase II, in biopsy samples taken from patients with invasive carcinoma of no special type. RPB1 frequently aggregates co-translationally in the absence of proper HSP90 chaperone function or in ribosome mutant cells as revealed formerly in yeast. We found that cytoplasmic foci of RPB1 occur in larger sizes in tumors that showed no regression after therapy. Based on these results, we propose that monitoring the cytoplasmic aggregation of RPB1 may be suitable for determining - from biopsy samples taken before treatment - the effectiveness of neoadjuvant chemotherapy.

cancer biology↗

bioRxiv2021

Old players in new posts: the role of P53, ATM and DNAPK in DNA damage-related ubiquitylation-dependent removal of S2P RNAPII

DNA double-strand breaks are the most deleterious lesions for the cells, therefore understanding the macromolecular interactions in the DNA repair-related mechanisms is essential. DNA damage triggers transcription silencing at the damage site, leading to the removal of the elongating RNA polymerase II (S2P RNAPII) from this locus, which provides accessibility for the repair factors to the lesion. Ataxia-telangiectasia mutated (ATM) and DNA-dependent protein kinase (DNAPK) are the two main regulatory kinases of homologous recombination and non-homologous end joining, respectively. Although these kinases are involved in the activation of different repair pathways, they have common target proteins, such as P53. We previously demonstrated that following transcription block, P53 plays a pivotal role in transcription elongation process by interacting with S2P RNAPII. In the current study, we reveal that P53, ATM and DNAPK are involved in the fine-tune regulation of the ubiquitin-proteasome system-related degradation of S2P RNAPII. However, they act differently in this process: P53 delays the removal of S2P RNAPII, while ATM and DNAPK participate in the activation of members of E3 ligase complexes involved in the ubiquitylation of S2P RNAPII. We also demonstrate that WW domain-containing protein 2 (WWP2) and Cullin-3 (CUL3) are interaction partners of S2P RNAPII, thus forming a complex with the transcribing RNAPII complex. Simple SummaryTo ensure the proper repair following DNA double-strand breaks, the eviction of the arrested elongating RNA polymerase II (S2P RNAPII) is required. Here, we report an emerging role of P53, Ataxia-telangiectasia mutated (ATM) and DNA-dependent protein kinase (DNAPK) in the ubiquitin-proteasome system-dependent removal of S2P RNAPII. We also identified interactions between S2P RNAPII and WW domain-containing protein 2 (WWP2) or Cullin-3 (CUL3) (members of E3 ligase complexes), which are involved in the ubiquitylation of S2P RNAPII following DNA damage. Furthermore, the RNAPII-E3 ligase complex interactions are mediated by P53, ATM and DNAPK, which suggests potential participation of all three proteins in the effective resolution of transcription block at the damage site. Altogether, our results provide a better comprehension of the molecular background of transcription elongation block-related DNA repair processes and highlight an indispensable function of P53, ATM and DNAPK in these mechanisms.

molecular biology↗

bioRxiv2019

Quantification of DNA damage induced γH2AX focus formation via super-resolution dSTORM localization microscopy

In eukaryotic cells, each process, in which DNA is involved, should take place in the context of chromatin structure. DNA double-strand breaks (DSBs) are one of the most deleterious damages often leading to chromosomal rearrangement. In response to environmental stresses, cells have developed repair mechanisms to eliminate the DSBs. Upon DSB induction, several factors play roles in chromatin relaxation by catalysing the appropriate histone posttranslational modification (PTM) steps, therefore promoting the access of the repair factors to the DSBs. Among these PTMs, the phosphorylation of the histone variant H2AX at its Ser139 residue (also known as {gamma}H2AX) could be observed at the break sites. The structure of {gamma}H2AX focus has to be organized during the repair as it contributes to accessibility of specific repair proteins to the damaged site. Our aim was to develop a quantitative approach to analyse the morphology of individual repair foci by super-resolution dSTORM microscopy to gain insight into genome organization in DNA repair. We have established a specific dSTORM measurement process by developing a new analytical algorithm for gaining quantitative information about chromatin morphology and repair foci topology at individual {gamma}H2AX enriched repair focus. By this method we quantified unique repair foci to show the average distribution of {gamma}H2AX clusters. By monitoring {gamma}H2AX signal, we could reach 20 nm spatial resolution and resolve a single DNA damage spot, which allow us to identify different chromatin sub-clusters around the break site. Additionally, based on our new analysis method, we were able to show the number of nucleosomes in each sub-cluster that could allow us to define the possible chromatin structure and the nucleosome density around the break sites. This method is the first demonstration of a single-cell based quantitative measurement of a discrete repair focus, which could provide new opportunities to categorize spatial organization of dot patterns by parametric determination of topological similarity.

cell biology↗