Call for Speakers 2025

Small molecule inhibitors targeting Siglec-15 are not explored alongside characterised regulatory mechanisms involving microRNAs in CRC progression. Therefore, a small molecule inhibitor to target Siglec-15 was elucidated in vitro and microRNA-mediated inhibitor effects were investigated. We demonstrated that the SHG-8 molecule exerted significant cytotoxicity on cell viability, migration, and colony formation, with an IC50 value of 20µM. Notably, miR-6715b-3p was the most upregulated miRNA via high-throughput sequencing, which was validated via RT-qPCR. Additionally, molecular docking studies revealed SHG-8 interactions with the Siglec-15 binding pocket with the binding affinity of -5.4 kcal/mol, highlighting its role as a small molecule inhibitor. Importantly, Siglec-15 and PD-L1 are expressed on mutually exclusive cancer cell populations, suggesting the potential for combination therapies with PD-L1 antagonists.

Liquid biopsy-based nucleic acid diagnostics (LD) is transformative in clinical diagnostics, yet oncological LD development predominantly relies on clinical samples, yielding limited correlative insights. Functional precision oncology, integrated to disease modeling (DM), bridges clinical-experimental gaps, offering mechanistic understanding to discern tumor therapy resistances and inflammation effects beyond perfusion imaging. Aligned with 3R principles, our focus on low 5-year survival rate tumors employs NGS to assess RNA content in cancer stem cells (CSC) and their disease model environments (DME). Diverse computational tools and machine learning discover potential CSC-RNA sheddome candidates, empowered by coherent epigenomic signals shared between in vitro and animal models. This provides therapy optimization insights, prompting a reconsideration of the necessity for animal perfusion studies in early LD development.

This work introduces an innovative RNA detecting method using bespoke fluorescence nanoprobes. These nanoprobes, comprised of plasmonic nanoparticles functionalized with fluorophore-labeled thiolated ssDNA, specifically target cancer biomarker RNA. Fluorescence intensity and lifetime of the nanoprobes were sensitive to the level of target RNA. Spatial maps of intracellular target RNA were generated using fluorescence lifetime imaging microscopy and rapid fluorescence lifetime analysis, distinguishing cancer cells with elevated target RNA levels from control cells. The nanoprobes effectively detected target RNA in cell-derived exosomes, differentiating cancer exosomes from healthy ones. We also demonstrated their potential for single-cell intracellular RNA detection in cell models and clinical samples using flow cytometry, emphasizing their value for rapidly identifying cancer biomarker RNAs in liquid biopsies.

Glioblastoma multiforme (GBM) is an aggressive brain malignancy with current treatments resulting in poor prognoses. β-amino carbonyl compounds (β-ACs) have gained attention due to their potential anti-cancerous properties. In vitro assays were performed to evaluate the effects of an in-house synthesised β-AC compound, named SHG-8, upon GBM cells. Small RNA-sequencing (sRNA-seq) and biocomputational analyses investigated SHG-8’s effects upon the miRNome and its bioavailability within the human body. SHG-8 exhibited significant cytotoxicity in U87MG cells, inhibiting migration, proliferation, and inducing apoptosis. sRNA-seq revealed a dramatic shift in miRNA expression upon SHG-8 treatment and significant downregulation of miR-21. RT-qPCR demonstrated a significant downregulation of CORO1C, a target gene of miR-21. Therefore, SHG-8's inhibitory effects on GBM cells may involve mi R-21-mediated CORO1C inhibition.

The main objective of this study is to explore data assimilation techniques for predicting malignant brain tumor growth, focusing on glioblastoma. We use MRI images as crucial observation data and integrate them into our numerical model using data assimilation methodologies. By assimilating the MRI observations into our model, we aim to provide accurate and up-to-date estimates of the tumor's state and forecast its development and progression over both short-term and long-term periods. We introduce two pivotal data assimilation operators, the Volume Element Data Assimilation Operator (VEDA) and the Nodal Point Operator (DANP), which enhance the accuracy and reliability of the tumor growth forecasts. Our research provides the existence and uniqueness of solutions and validates the convergence of the data assimilation algorithm. Accurate predictions of malignant brain tumor growth, particularly glioblastoma, hold significant clinical implications for treatment planning and patient guidance, potentially leading to improved treatment strategies and patient outcomes in brain cancer management.

Cancer metastasis is the most lethal attribute of cancer. We identified the novel, previously undescribed gene Metastasis-Associated in Colon Cancer 1 (MACC1) induces fundamental processes like cell proliferation, migration, invasiveness and metastasis. MACC1 has been established as key player, prognostic and predictive biomarker for tumor progression and metastasis in >20 solid cancers. We identified repositioned drugs and novel compounds as transcriptional and post-translational small molecule inhibitors, restricting MACC1-induced metastasis in mice. All these endeavors are performed in translational approaches by bridging our experimental data to their clinical relevance and clinical use of patient tumor tissue and patient blood. The ultimate goal is the signaling-based establishment of new therapeutic concepts for metastasis restriction and prevention.

Pancreatic cancer leads to a poor life expectancy (4-6 months) due to its silent nature. Thus, an early detection strategy would save a large number of lives. We focus on glycoprotein mucin 1 (MUC1), which is overexpressed in 90% of cancers while patients generate antibodies against it. We have developed a very sensitive detection system for these antibodies by generating an unnatural peptide with higher affinity for the antibodies, and binding the unnatural peptides to gold nanoparticles. In a clinical study, we found significant differences between pancreatic cancer patients and healthy volunteers (p <0.0001). A ROC analysis produced an area under the curve of 0.918, with 85% sensitivity and 90% specificity. We are looking for partners to commercialize this detection system.

This cross-national study investigates and contrasts validation standards for early cancer detection biomarkers during regulatory approvals across the United States, Europe, Japan, and South Korea. Analyzing criteria set by regulatory bodies in each country, the research delves into healthcare infrastructure, regulatory benchmarks, and technological evaluations. The study sheds light on disparities in validation standards. Thorough analysis of regulatory guidelines and case studies informs the examination of early cancer detection biomarker validation processes. The study aims to enhance understanding of cross-national differences and promote international cooperation, contributing to the advancement of early cancer detection globally.

Using next generation sequencing (NGS) we showed that small RNA (sRNA) biomarkers are indicative of early lung cancer (Sikosek et al, 2023, JTO). Currently, we are transitioning the signature detection to digital PCR (dPCR) platforms, which enabled us to explore and utilize multiple aspects of RNA biomarkers’ biology, such as post-transcriptional modifications. dPCR outperforms NGS by both costs and sensitivity, while broadening the applicability in clinical settings. We will present details of streamlined platform based on sRNAs extracted from biological fluids that can be applied for both discovery and testing. We will discuss the technological advances applied to enable the usage of sRNAs as viable biomarkers for cancer detection.

Thyroid nodules are frequent but mostly benign, and postoperative rate of benign nodules reaches 90%. Therefore, there is a need for identification of reliable preoperative diagnosis markers for patients with thyroid cytology. In particular, there is a gap in studies of interrelationships between diurnal profiles of expression of circadian clock genes and TSH receptor in thyroid tissue exposed to different concentrations of TSH. These interrelationships might be investigated in future in vitro experiments on benign and malignant thyrocytes cultivated under normal and challenged TSH levels. Results of this investigation might help to bridge previous studies of preoperative biomarkers for thyroid carcinoma that explore diagnostic value of diurnal profiles of serum TSH levels, expression of its receptor and circadian clock genes.

Proper stratification of patients with high risk of relapse in early stage of estrogen-positive breast cancer is a known clinical problem. HAX1 protein has been described by our group as an important factor implicated in progression and metastasis of breast cancer. Diagnostic potential of HAX1 IHC staining of primary tumor samples in prediction of distant metastasis may be comparable with Oncotype DX multiple genes recurrence score assay. If further substantiated, HAX1 IHC staining may be a new, simple in use and inexpensive prognostic factor of disease recurrence in luminal breast cancer.

About 25% of stage II colon cancers relapse within 5 years in the absence of adjuvant chemotherapy. We identify major markers of risk of relapse within a homogeneous population of stage II, pT3N0 microsatelitte-stable colon cancers and show that a gene-expression predictive signature could be used to identify the candidate patients for chemotherapy.

The presentation will delve into the utilisation of microRNA expression as biomarkers for the early detection of PDAC. This research study will concentrate on a selection of microRNAs to elucidate their functions and significance in the context of PDAC by using in vitro and in vivo data.