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Save the Date: 21-22 November. Berlin, Germany.
The Berlin Early Cancer Forum (E-C-Forum) will bring together leading experts in cancer risk, early detection, prevention, molecular diagnostics, and data science to share groundbreaking research and progress in the field, explore the challenges and opportunities of emerging technologies for early cancer detection, screening, and precision diagnosis.
Integrated, interdisciplinary collaboration is key to bringing new ideas to address the challenges of early cancer detection. The sessions aim to connect researchers in the early cancer detection and diagnosis space to spark conversation and collaboration. It will also become an opportunity to showcase the latest trends and innovations in molecular diagnostics and the cutting-edge applications of data science in cancer medicine and research.
Sessions include:Last updated on 06.09.2023 | The listing of a proposal does not imply an approval of a presentation. The final programme will be released here closer to the event.
Previously, detection and quantifying DNA methylations have relied on conversions of DNA mainly using bisulfite, which is a time-consuming and labor-demanding procedure, requiring a high quantity of DNA. Our new and innovative qPCR technology, EpiDirect® allows for direct quantification of cytosine methylation using natural untreated DNA. In just two hours, methylated DNA is amplified by a special primer, EpiPrimer™, which has a high affinity for methylated cytosines, thus allowing selective amplification of methylated DNA over unmethylated DNA. We show results from the CE-IVD EpiDirect® MGMT Methylation qPCR Assay and the EpiDirect® MLH1 Assay which is currently under development. EpiDirect® MGMT detects and quantifies from 100% to 3% methylated DNA, and preliminary results from the EpiDirect® MLH1 show equally promising potential.
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.
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.
Information regarding a hand-held, real-time fluorescence detection device will be presented along with the development of a simple sample collection and analysis system. The sample, like a swab, goes into a standard flexible tube and a few drops are squeezed into two standard PCR tubes (with lyophilized reagents) in a holder and the holder is placed in the device. No cartridges or DNA or RNA purification steps are necessary. The Start button is pressed to initiate the reaction. Data is displayed at the end of the run on a LED bar, indicating an intuitive positive, not detected, or invalid result. The device provides a quantitative Ct value. The system is also capable of detecting mutations and therefore can be used for detection of single gene genetic diseases.
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.
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 levels, chemical modifications, and relative ratios of biomolecules circulating in systemic bioliquids, like blood plasma, are indicators of various physiological and pathological states. Capitalizing on broadband optics, ultrafast laser sources, and precision femtosecond-attosecond field-resolving technologies, we recently developed electric-field molecular fingerprinting (EMF) to detect changes in molecular composition of bioliquids, establishing EMF as a new in vitro diagnostic analytical technique to uncover characteristic molecular traces of diseases in blood samples. EMF, as advanced infrared spectroscopy, has the inherent capacity to sensitively and robustly probe across different types of chemical bonds and molecular classes within one measurement, providing deep cross-molecular description of physiological states. Here, we present data from our multi-centric multi-cancer study in which we analyzed infrared molecular fingerprints of plasma and serum from several thousands of individuals, involving cancer patients with different solid tumors and matched reference individuals. Focusing on four common cancers - breast, bladder, prostate, and lung cancer - we find that infrared molecular fingerprinting is capable of detecting therapy-naïve malignant conditions. Employing machine learning data analytics, we obtain binary classification performances in the range of 0.78–0.89 (area under the receiver operating characteristic curve [AUC]), and additionally demonstrate correlation between AUC and tumor load. Intriguingly, we find that the spectral signatures differ between different cancer types, thus allowing to distinguish between different cancers in a single measurement. Our studies lay the foundation for using EMF in health monitoring, in particular for onco-infrared-fingerprinting, providing a novel high-throughput, cost-effective technology platform that can be used as a complementary analytical tool for cancer detection and screening.
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.
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.