Project description:The transcriptomic heterogeneity of the prostate cancer was tested by profiling histologically distinct but equally graded (Gleason score 4+5=9/10) cancer nodules from a surgically removed prostate cancer. We found that not only that the genes were differently regulated in the two nodules but also that expression fluctuations were differently controlled and the gene networks differently remodeled.
Project description:Prostate cancer is characterized as being histologically and molecularly heterogeneous. Additionally, epigenetic changes play an important role in regulating the progression of prostate cancer. However, epigenetic intraindividual heterogeneity is largely unknown in advanced prostate cancer. Hence, the epigenetic profiles of advanced prostate cancer, including autopsy cases, were investigated.
Project description:Prostate cancer is characterized as being histologically and molecularly heterogeneous. Additionally, epigenetic changes play an important role in regulating the progression of prostate cancer. However, epigenetic intraindividual heterogeneity is largely unknown in advanced prostate cancer. Hence, the epigenetic profiles of advanced prostate cancer, including autopsy cases, were investigated.
Project description:This project introduces a spatial multi-omics (SMOx) pipeline integrating MALDI-2 mass spectrometry imaging (MSI) with Visium spatial transcriptomics (ST) and single-nucleus RNA sequencing (snRNA-seq) to investigate molecular heterogeneity in human prostate cancer (PCa). MALDI-2 MSI was used to map lipid distributions with enhanced sensitivity compared to conventional MALDI, enabling detailed visualization of metabolic alterations across tissue regions. Through non-rigid co-registration via H&E images and Gaussian-weighted granularity matching, MSI data were spatially aligned with transcriptomic and histological layers. This integration revealed lipidgene expression relationships associated with distinct cell populations and pathological states within heterogeneous prostate tissues. The resulting dataset provides a high-resolution molecular atlas of PCa, demonstrating the power of MSI-driven spatial multi-omics to uncover lipid-based signatures that refine tissue annotation and support molecular pathology studies.
Project description:Prostate cancer is characterized as being histologically and molecularly heterogeneous. Additionally, epigenetic changes play an important role in regulating the progression of prostate cancer. However, epigenetic intraindividual heterogeneity is largely unknown in advanced prostate cancer. Hence, the epigenetic profiles of advanced prostate cancer, including autopsy cases, were investigated.
Project description:Prostate cancer is the second most occurring cancer in men worldwide, and with the advances made with screening for prostate-specific antigen, it has been prone to early diagnosis and over-treatment. To better understand the mechanisms of tumorigenesis and possible treatment responses, we developed a mathematical model of prostate cancer which considers the major signalling pathways known to be deregulated. The model includes pathways such as androgen receptor, MAPK, Wnt, NFkB, PI3K/AKT, MAPK, mTOR, SHH, the cell cycle, the epithelial-mesenchymal transition (EMT), apoptosis and DNA damage pathways. The final model accounts for 133 nodes and 449 edges. We applied a methodology to personalise this Boolean model to molecular data to reflect the heterogeneity and specific response to perturbations of cancer patients, using TCGA and GDSC datasets.
Project description:Prostate cancer is characterized as being histologically and molecularly heterogeneous. Additionally, epigenetic changes play an important role in regulating the progression of prostate cancer. However, epigenetic intraindividual heterogeneity is largely unknown in advanced prostate cancer. Hence, the epigenetic profiles of advanced prostate cancer, including autopsy cases, were investigated.