Andrey Klymchenko’s Post

❓What is the relatively easy and cheap way of genotyping of large amount of samples? 🎯In IRA3P we have long experience in using and analyzing DNA microarrays, called also DNA chips, which is the collection of microscopic DNA spots attached to a solid surface. The basic principle behind microarrays is hybridization between two DNA strands, the property of complementary nucleic acid sequences to specifically pair with each other by forming hydrogen bonds between complementary nucleotide base pairs. We use Global Screening Array to determine differences in the genetic make-up of an individual by examining her/his DNA sequence using biological assays and comparing it to another individual's sequence or a reference sequence. This way we compare DNAs originating from tumor fragments with seemingly normal tissue surrounding the tumor to the reference DNAs from blood, to find and identify post-zygotic mutations. 💡The arrays provide an excellent tool for clinical research applications including disease risk profiling studies, complex disease discovery, identification of pathogenic unbalanced chromosomal aberrations and has been commonly used in genetic diagnostics. ➡️ If you want to know how we used microarrays technology in our study, check our papers in which we utilized it: https://lnkd.in/dSmga7GG https://lnkd.in/dixZvA9C https://lnkd.in/dw-mxAGr https://lnkd.in/d9QnfEae

This preprint features a combined approach using Visium HD, Chromium Single Cell (Flex and Immune Profiling), and Xenium In Situ analysis for deepened insights into immune cell composition within the tumor microenvironment of colorectal cancer.

A year ago, somebody asked me: don't we already know everything there is to know about PI3K signalling - so shouldn't you be changing research topic? My answer was released over Christmas: check out our preprint which prompts a revision of our thinking about PI3K signalling and the perturbations caused by one of the most common oncogenic mutations, PIK3CA-H1047R. https://lnkd.in/gx4fKVhZ During my Sir Henry Wellcome fellowship, I devoted most of my wake hours to the development of reproducible, quantitative assays for single-cell measurements of PI3K signalling activity. These assays were crucial for discovering that oncogenic PIK3CA-H1047R is not a simple PI3K pathway activator but instead acts to blur growth factor-specific signal transfer - somewhat like crossed wires or blurred vision! We also demonstrate that PI3K signalling outputs are probabilistic which is impossible to capture with the standard bulk signalling assays in common use. Our findings have implications for pharmacological targeting of oncogenic PI3K signalling and our basic understanding of this fundamental cellular pathway.

N-myristoylation is a targetable vulnerability of senescent cells Very excited to see our work at Imperial College London and The Francis Crick Institute, led by Jesus Gill at MRC Laboratory of Molecular Biology (LMB) at Imperial College London with colleagues across the world, published in Nature Cell Biology, reporting the discovery of N-myristoyltransferase (#NMT) as a druggable vulnerability in senescence. https://lnkd.in/dDHFGGZZ Senescent cells are a key driver of aging and tumour progression. Our contribution established the extraordinarily potent senolytic (selective senescent cell killing) effects of NMT inhibitors discovered in our labs, and further developed by Myricx Bio, who are driving the development of first in class #NMT inhibitor-Antibody conjugates (#ADCs) for targeted #cancer #therapy. Check out the paper for the elegant underlying mechanism which involves inhibition of a novel ER-Golgi trafficking vulnerability in senescent cells, elaborated in exquisite detail by Jesus and colleagues.

We are partnering with National Science Foundation (NSF) to award $15.4 million in funding for research to help understand RNA biology and develop RNA-based technologies! https://lnkd.in/ejjjgcPh Researchers will focus on the structures, functions and interactions of RNA. They will also expand the capabilities of sequencing technologies to determine the sequence of any RNA molecules, including those with modifications that are difficult to detect. RNA is a molecule that is in all living cells and plays a role in nearly all biological processes, including carrying instructions for making proteins, helping build proteins and turning genes on and off. While RNA was discovered over a century ago, researchers are still uncovering new RNA-related pathways and RNA structures. Recent scientific advances have harnessed RNA to develop technologies and therapeutics such as small interfering RNA-based drugs and messenger RNA-based vaccines against cancers and infectious diseases. Learn more! https://lnkd.in/ejjjgcPh

A novel technology for single-cell RNA sequencing Recently, researchers from A*STAR's Genome Institute of Singapore have developed Sc-SPORT, a novel method for single-cell RNA sequencing, revealing the varied structures of RNA in individual cells which may influence their functions. This groundbreaking approach, published in Nature Methods, allows for the identification of biomarkers for human development and disease based on RNA shape. This research was led by Dr. Wan Yue and Dr. Jiaxu Wang, the technique in the paper offers a new perspective on cellular identity and the potential for RNA structure to act as biomarkers or drug targets, particularly in diseases where RNA levels remain constant. This method enhances the understanding of RNA's role in individual cells, and providing valuable insights for RNA virus research, including COVID-19. Therefore, this research has implications for improved biomedical science and disease treatment strategies. (See https://lnkd.in/eftNzKnm for details)

Time is of the essence for diagnosing cancer patients and NICU/PICU babies. GenomeArc HORIZON™, optimized for regular servers, produces unprecedented variant classification and pharmacogenomic insights from whole genome sequencing variants (>5 million) in just a few minutes. 📚 GenomeArc HORIZON™ enables diagnosis by producing ACMG-guided variant classification in a few minutes using validated and published tertiary algorithms. 📚 The pharmacogenomics and rare disease language model produces unparalleled insights for therapeutic options. 📚 GenomeArc HORIZON™ helping clinicians and scientists processing thousands of analyzed genome across the globe. To demo GenomeArc HORIZON™ : https://lnkd.in/dQpCct4V For more about GenomeArc HORIZON™, please read: https://lnkd.in/dFdgNzXS #AcceleratingMedicine #PrecisionMedicine #CancerGenomics #NICU #PICU #rarediseases

Role of long-noncoding RNA in diabetic atherosclerosis Diabetes accelerates the development of atherosclerosis, increasing the incidence of cardiovascular events. In atherosclerosis, immune cells called macrophages release molecules such as chemokines and cytokines, causing inflammation and leading to arterial plaque formation. However, significant gaps persist in understanding the exact molecular mechanisms controlling this increased inflammatory response in individuals with diabetes. In a new, preclinical study, researchers identified a long non-coding RNA (lncRNA) sequence that could help them unravel the complex processes underlying diabetic atherosclerosis, potentially paving the way for future therapeutic interventions in humans. Through genetic analysis of a mouse model of diabetic atherosclerosis, the research team identified a specific sequence of long-noncoding RNA, they named MERRICAL, which is involved in recruiting macrophages to the arterial wall. As atherosclerosis progressed in these mice, the researchers found a notable increase in the expression of MERRICAL at arterial lesions—areas where atherosclerosis plaque built up and damaged the arteries. #ScienceMission #ScienceNewsHighlights https://lnkd.in/gyPzACqq

Excited to share the first research article from my group at Memorial Sloan Kettering Cancer Center. Together with Tsion A., Robert Mohajeri-Stickels, Meril Takizawa, Ronan Chaligné, and Ansuman Satpathy, we develop PERFF-seq, a new technology for the combinatorial and programmable enrichment of cells and nuclei upstream of scRNA-seq, particularly on the 10x Genomics platform. We think that this method will be particularly useful for studying heterogeneity in rare cell populations that likely underlie complex diseases. Check it out and let us know what you think! https://lnkd.in/en_BCMSb Also check out our data/ protocol resources: https://lnkd.in/e45ja_Fi

There is no better way to greet the new year than seeing this collaborative work finally published in the first issue of Science in 2024! https://lnkd.in/g965T_nk This study is led by Dr. Nunez, who developed a robust immune-related adverse events (irAE) mouse model by colonizing mice with the microbiota isolated from wild-caught mice. We employed our robust supervised capacity preserving mapping (supCPM) single-cell visualization tool to identify a unique mechanism of anti-CTLA4-mediated irAE. Anti-CTLA4 immune checkpoint blockade selectively depletes peripherally induced regulatory T-cells (pTregs) but not thymic-derived Tregs, the latter of which features high expression levels of Helios. Anti-CTLA4-mediated colitis is mediated by Fcgamma receptor signaling because an anti-CTLA4 nanobody induced an anti-tumor immune response without inducing colitis. In this effort, when we analyzed both human and mouse T-cell subsets, we continued to observe the benefits of using supCPM over UMAP for rendering the 2-dimensional projection of clusters. UMAP has two noted limitations. The first is that the cluster size is often driven by the number of cells. The second is that the geographic distance on a UMAP does not always correlate with biological distance. The cluster sizes on a supCPM rendering are largely driven by gene expression variance. The functionally similar clusters are more closely grouped for annotation. We analyzed the exact same data using both methods, as shown in the attachment. We look forward to seeing how supCPM can continue to propel our understanding of functionally similar yet distinct immune cell subsets.