Biology subjects

Hu-Lieskovan, S.

Publications and source records attributed to Hu-Lieskovan, S..

3 recordsLinked to original sources

bioRxiv2025

Genetic Drivers of Sensitivity or Resistance to RAS(ON) Multi-Selective Inhibitors in NRAS-Mutated Melanoma

Most patients with advanced BRAF or NRAS-driven melanoma receive front-line immunotherapy. However, if immunotherapy fails, BRAF-mutated patients have effective second-line therapies, whereas NRAS-mutated patients lack pathway-targeted options. Recently, RAS(ON) multi-selective inhibitors like RMC-7977, and the investigational agent daraxonrasib, were described that, in partnership with cyclophilin-A (CYPA), inhibit RAS[GTP] signaling. Both compounds demonstrate potent anti-proliferative activity against NRAS-mutated melanoma cell lines and robust anti-tumor activity against preclinical melanoma models. However, in preclinical models, resistance to RMC-7977 monotherapy arose through mutations in Ppia (encoding CYPA) or Map2k1 (encoding MEK1). Moreover, two clinical case studies in patients with NRAS-mutated melanoma treated with daraxonrasib demonstrated clear anti-tumor activity in one patient, but progressive disease in another with co-occurring NRAS and MAP2K1 mutations at baseline. These findings support the potential for daraxonrasib in treatment of patients with NRAS-mutated melanoma, and reveal candidate mechanisms of monotherapy resistance, underscoring the need for combination therapies to improve outcomes. SIGNIFICANCEThere are no pathway-targeted therapies for patients with NRAS-mutated melanoma. Here we demonstrate that direct pharmacological inhibition of RAS[GTP] with RMC-7977 or daraxonrasib (RMC-6236) has profound inhibitory effects in preclinical models of NRAS-mutated melanoma. Furthermore, we identify mechanisms of resistance to RMC-7977 through mutational inactivation of CYPA or mutational activation of MEK1.

cancer biology↗

bioRxiv2025

Comparison of QuPath and HALO platforms for analysis of the tumor microenvironment in prostate cancer

QuPath, an open-source digital pathology platform, has gained widespread use for image analysis in biomedical research since its release in 2016. However, its reproducibility and reliability compared to commercial software, such as HALO, requires further validation, particularly for multiplex immunofluorescence (mIF) analysis. In this study, we performed a direct comparison of QuPath and HALO using a mIF-stained prostate cancer tissue microarray (TMA) inclusive of 192 unique cores. We evaluated performance across three key analytical modules: immune cell phenotyping, tumor infiltration with immune cells, and nearest neighbor analysis. Furthermore, we integrated QuPath with CytoMap, an open-source spatial analysis tool, to perform unsupervised clustering of immune cell infiltration--a feature not available in HALO. Our results demonstrated high concordance between two platforms, with correlation coefficients exceeding 0.89 for immune cell density, distance and pattern of cell organization in tumor microenvironment (TME). A neighborhood analysis using CytoMap was further performed and provided a more detailed spatial analysis of immune cell distribution across different prostate cancer grades. A significant increase of CD103+ T cell infiltration into TME was observed in prostate cancer, which might be associated with the expression level of its ligand (E-cadherin) in the tumor region. In conclusion, our findings validate QuPath as a robust and reproducible alternative to commercial platforms for fluorescence-based digital pathology. By demonstrating QuPaths capability to perform high-quality quantitative analysis with additional flexibility for integration with external tools, our study underscores its potential for advancing tumor microenvironment research in translational oncology.

pathology↗

bioRxiv2020

Optimizing nucleic acid extraction and transcriptome evaluation from low-input, fixed clinical samples

Tumor biopsies are commonly formalin-fixed and paraffin-embedded (FFPE) for long-term and efficient storage. However, FFPE preservation can greatly compromise the quality of samples, the extraction of nucleic acids, and feasibility of downstream studies, including RNA sequencing. These challenges are especially evident in the studies of clinical trial samples, where the sizes of biopsies often limit the amount of material available for study. Here, we evaluate two nucleic acid extraction kits (Covaris truXTRAC FFPE tNA Plus, QIAGEN miRNeasy FFPE) and three hybridized-capture-based RNA sequencing library preparations (Agilent SureSelect XT RNA Direct, Agilent SureSelect XT HS, and Illumina TruSeq RNA Exome) to evaluate the impact of these sample processing steps on transcriptome evaluation in a melanoma biopsy procured in a clinical setting and preserved by FFPE. While there exist many options for extraction and library preparation that are appropriate for RNA sequencing from FFPE samples, we observed that combinations of experimental approaches may have subtle impacts on downstream analysis, including gene expression quantification and fusion detection.

genomics↗