Ahmet F Coskun’s Post

#LearningWednesday time! Tumor tissues are complex environments; however, existing platforms often overlook spatial context. Integrating advanced techniques allows for comprehensive mapping of the tumor-immune microenvironment (TIME), revealing insights into cellular neighborhoods and facilitating personalized treatment strategies by understanding tissue structures in 3D. https://lnkd.in/dHG49rXX “A tumor tissue is composed of not only cancer cells but also other cell types and microorganisms that communicate among themselves in a three-dimensional (3D) space to support cancer cell growth.” “Understanding how cancer cells communicate with other cell types in the 3D space of the tumor tissue will allow for the identification of new therapeutic targets for the treatment of these diseases.” “Most platforms used for the molecular reconstruction of the tumor–immune microenvironment (TIME) of a solid tumor fail to explore the spatial context of the three-dimensional (3D) space of the tumor at a single-cell resolution, and thus lack information about cell–cell or cell–extracellular matrix (ECM) interactions. “ “We integrated multiple new techniques using a suite of newly developed analytical methods to simultaneously identify expression of genes, metabolites, and proteins in single tissue ‘voxels’.” “These platforms include non-targeted mass spectrometry imaging (glycans, metabolites, and peptides) and Stereo-seq (spatial transcriptomics) and targeted seqIF (IHC proteomics).” “We demonstrated that features, adjacent cells, vessels, etc., are closer in the Z dimension than in the X and Y dimensions. This speaks to the fact that clustering or neighborhoods are not two-dimensional objects they occupy a three-dimensional space. This means that many of the finding related to the relevance of immuno-supportive or immuno-suppressing may not be found in the same plane, but in the planes above or below. “ “Mapping tumors and precancerous lesions is critical in personalizing medical treatments to the environments found in each patient and holds the best promise for the optimal outcome for that patient. This means an understanding of which cells are present, what their functional statuses are, and how they are energized is critical to understanding how a patient’s disease will progress and inidentifying the aforementioned optimal treatment. In this manuscript, we have demonstrated an integrated multiplex multi-omics methodology to generate a three-dimensional tissue map of multiple tissues.” “By examining the 3D structure of the tissue and understanding how cellular neighborhoods are constructed, we have a more comprehensive understanding of the TIME. We have also mitigated the weaknesses of any single technology by leveraging the strengths of an adjacent technology to build a comprehensive map of the TIME.”

Dear LinkedIn Network, The time has come for me defend my thesis research from these past 5 years at Stanford! If you're interested in hearing about spectral cytometry and cancer multiomics, feel free to attend virtually on March 20th, 2:30pm PST: https://lnkd.in/g9xh3TBa. Looking forward to seeing you there! Defense Abstract: High-dimensional tissue profiling on the axes of time, cell type, and treatment is necessary to unravel the heterogeneity within systems-wide responses to disease. We are witnessing a renaissance in the development of these methods, which have enabled greater parameterization, accuracy, and throughput than previously achieved for studying systems biology. We first utilize techniques in spectral cytometry to study the transfection efficiency of T cell targeted LNPs as a function of time and tissue. We packaged reporter gene mRNA into CD3-targeted LNPs and successfully transfected murine T cells in vivo that were capable of migrating to tumors in the presence of immunotherapy. While promising, we discovered a variety of consequences associated with anti-CD3 coating that sparked questions about immune subsets beyond T cells. These questions prompted us to engineer a 40-color deep immunophenotyping panel for murine lymphoid tissues and tumors. We used this tool to unlock insights into tissue leukocyte composition and immune response mechanisms to combinatorial immunotherapy. Only after achieving this level of resolution did we fully appreciate how the spatial organization of immune, stromal, and tumor cells could inform their function. To explore this, we harmonized 51-plex CODEX with Visium spatial transcriptomics to deconvolve pancreatic ductal adenocarcinoma microenvironments. These insights culminated in the development of an anti-Claudin-4 peptide PET probe for PDAC imaging in mice, and I conclude this talk with microdosimetry modelling techniques to aid in future theragnostic development for PDAC treatment.

🔬 Discovering breakthroughs through tumor tissue research! 🧬 Did you know that tumor tissue plays a vital role in advancing medical research? Here's why tumor tissue is of utmost importance: 1️⃣ Understanding disease progression: Tumor tissue provides valuable insights into the development and progression of various diseases, including cancer. By studying tumor tissue samples, researchers can uncover crucial information about the genetic mutations, cellular behavior, and signaling pathways associated with the disease. This knowledge is essential for developing targeted therapies and improving patient outcomes. 2️⃣ Personalized medicine: Each patient's tumor is unique, and studying tumor tissue allows for personalized treatment approaches. Through comprehensive analysis, medical professionals can identify specific biomarkers and genetic profiles within tumor tissue. This knowledge enables tailored treatment plans that consider individual variations, leading to better therapeutic outcomes and improved patient care. 3️⃣ Drug discovery and development: Tumor tissue serves as a valuable resource for drug discovery and development. Researchers can use tumor samples to test the effectiveness of potential new therapies and evaluate their impact on tumor growth and response. By studying tumor tissue, scientists can identify promising drug targets, assess drug resistance mechanisms, and optimize treatment strategies. 4️⃣ Advancing research techniques: Tumor tissue research drives innovation and advancements in various research techniques and technologies. The analysis of tumor tissue often involves cutting-edge methods such as genomic sequencing, proteomics, and bioinformatics. These techniques not only enhance our understanding of diseases but also pave the way for new diagnostic tools and therapeutic approaches. 5️⃣ Collaboration and knowledge sharing: Tumor tissue research promotes collaboration among scientists, clinicians, and institutions worldwide. Sharing tumor tissue samples and associated data fosters a collective effort to unravel the complexities of diseases. Collaborative research initiatives facilitate the exchange of ideas, accelerate discoveries, and ultimately lead to improved patient care globally. Harnessing the potential of tumor tissue research is pivotal in the pursuit of medical advancements and improved patient outcomes. By supporting and investing in this crucial field, we can contribute to a brighter future of healthcare for all. Together, let's unravel the mysteries of diseases and transform lives through the power of tumor tissue research! #tumortissue #cellsamples #frozenspecimens #tissuesamples

Judit Kisistók will defend her PhD thesis "Exploring the biology and clinical utility of circulating tumor DNA" on Tuesday, September 12th at 13:00 at Health - Aarhus University. Diagnosing, profiling, and monitoring #cancer has traditionally been based on the analysis of surgically resected tumor samples. In recent years, liquid biopsies have garnered interest as a minimally invasive supplement or alternative to this medical practice. Investigating the blood, specifically, the tumor-originated DNA fragments in the plasma, termed circulating tumor DNA (#ctDNA), enables researchers and oncologists to gain real-time insight into the qualitative composition and the quantity of the malignancy. Despite considerable research efforts in the field, the exact, cancer type-, histology-, and patient-specific biology behind ctDNA release remains poorly understood, posing a limitation to clinical adoption. The primary aim of this Ph.D. study was, therefore, to elucidate the process of ctDNA shedding by analyzing the biological contributors and clinical associates of ctDNA release across various cancer types and study designs. To explore the biology behind ctDNA release, we first investigated the biological drivers in a cohort of lung adenocarcinoma patients, subjected to multi-region transcriptomic and genomic profiling of their tumor. We found that ctDNA positive patients carried a distinct, differential phenotype compared to ctDNA negatives, characterized by high proliferation, and associated with aggressive disease. To further investigate the biology driving ctDNA release across other cancer types, we analyzed genomic, transcriptomic, and clinical data to uncover the biology of ctDNA release within the context of a colorectal cancer cohort. We found that ctDNA release in colorectal cancer appears to be driven by a multitude of contributors, most notably, tumor size and proliferative capacity. Finally, we investigated how genomic alterations may contribute to response to immunotherapy by analyzing longitudinal ctDNA data from a cohort of metastatic melanoma patients. We have found that patients with subpar response to therapy harbored a higher percentage of TERT mutations, indicating that this gene could potentially be used as a marker in the clinic. The assessment committee consists of Richard T. Bryan, Professor at the Institute of Cancer and Genomic Sciences, University of Birmingham, UK, Mads Thomassen, Professor at Department of Clinical Genetics, University of Southern Denmark and Joanna Kalucka, Associate Professor Department of Biomedicine, Aarhus University. Read more here: https://lnkd.in/eKY3DPxR Photo: AU Foto/Lars Kruse

Happy to share a new publication in Cell Press Cell Reports Medicine in collaboration with Dr. Aaron Weinberg's group at Case Western Reserve University School of Dental Medicine and Case Western Reserve University School of Medicine; and Anant Madabhushi's group, and many others. Dr. Weinberg relentlessly led this collaborative effort for many years. It is such an honor for my group to be a part of this team. Case School of Engineering at Case Western Reserve University Head and neck cancer, of which oral cancer is about 90%, is the seventh-most prevalent malignancy in the world, and developing countries are witnessing a rise in its incidence. In this paper, we describe a new functional biomarker, beta-defensin index (BDI), to early diagnose oral cancer. Highlights: •The BDI non-invasively distinguishes oral squamous cell carcinoma (OSCC) from benign lesions. •BDI calculates hBD3 (over)expression/hBD2 (under)expression to detect carcinoma in situ and OSCC. •A multi-center validation study yields sensitivity and specificity of 98% and 83%. •The BDI may be adapted to a point-of-care assay using intact cell microfluidics. This work was supported by:  National Institute of Dental and Craniofacial Research (NIDCR), National Cancer Institute (NCI), Ohio Department of Development, and Case Coulter Translational Research Partnership of Case Western Reserve University Department of Biomedical Engineering. Case Western Reserve University press release: https://lnkd.in/e9J-j4dP Cell Reports Medicine publication: https://lnkd.in/eQBic-pp

📃Scientific paper: Oncology and mechanics: landmark studies and promising clinical applications Abstract: Clinical management of cancer has continuously evolved for several decades. Biochemical, molecular and genomics approaches have brought and still bring numerous insights into cancerous diseases. It is now accepted that some phenomena, allowed by favorable biological conditions, emerge via mechanical signaling at the cellular scale and via mechanical forces at the macroscale. Mechanical phenomena in cancer have been studied in-depth over the last decades, and their clinical applications are starting to be understood. If numerous models and experimental setups have been proposed, only a few have led to clinical applications. The objective of this contribution is to propose to review a large scope of mechanical findings which have consequences on the clinical management of cancer. This review is mainly addressed to doctoral candidates in mechanics and applied mathematics who are faced with the challenge of the mechanics-based modeling of cancer with the aim of clinical applications. We show that the collaboration of the biological and mechanical approaches has led to promising advances in terms of modeling, experimental design and therapeutic targets. Additionally, a specific focus is brought on imaging-informed mechanics-based models, which we believe can further the development of new therapeutic targets and the advent of personalized medicine. We study in detail several successful workflows on patient-specific targeted therapies based on mechanistic modeling. Discover the rest of the scientific article on es/iode ➡️https://etcse.fr/Xfc

🔔 In-depth research on tumor immune microenvironment 🔊 To overcome the limitations of IHC, IF, and single-cell analysis technologies in terms of throughput or spatial structural integrity of samples, scientists, Sophia Scheuermann and Christian Seitz from the University of Tübingen in Germany published an article titled "Unveiling spatial complexity in solid tumor immune microenvironments through multiplexed imaging", in the journal "Frontiers in Immunology". 🔊 In this article, researchers used the MACSima™ spatial biology platform and a 121 marker panel designed by the laboratory to analyze cancer cells, immune cells, and stromal cells in tumor samples. In-depth characterization analysis was performed to accurately describe the spatial distribution heterogeneity of immune cells in the tumor microenvironment and their spatial interaction with tumor cells. 📝 This study uses the Miltenyi Biotec #MACSima spatial biology platform to break through the constraints of traditional methodologies such as IHC and IF in biomarker analysis throughput by using immunofluorescence cyclic staining technology, and 📝 solves the limitation of single-cell analysis technology that cannot preserve tissue integrity. Link to the publication: https://lnkd.in/eAktiayx #spatialbiology #spatialproteomics

Localized predictions provide an additional benefit in understanding tissue heterogeneity. Levy-Jurgenson et al. developed a model to predict mRNA and miRNA expression from WSIs. The heatmaps produced are interesting, which they refer to as molecular cartography. But even more compelling is how they were able to quantify heterogeneity. Examining a small set of genes at a time, they displayed the model predictions over the slide, coloring each region based on the predictions. In the case of 2 genes, there were distinct colors for positive/positive, positive/negative, and negative/positive. To quantify heterogeneity, they computed the fraction of the slide belonging to each group and applied Shannon's entropy formula. High heterogeneity was found to be linked with poor survival, especially for breast cancer. Jaber et al. used deep learning to predict Basal versus Luminal A genomic subtypes of breast cancer. The image-based biomarkers were found to be more predictive of patient survival than the molecular subtypes themselves. Further, the heterogeneous samples -- predicted to contain both Basal and Luminal A subtypes -- had an intermediate prognosis. Bychkov et al. also demonstrated that their image-based model can predict patient outcomes. They trained their model to predict breast cancer HER2 status and demonstrated that these predictions were also associated with survival and treatment response. Read this article thoat I wrote to learn how to create deep learning models to predict molecular biomarkers from histology. https://ed.gr/eabhz #Pathology #CancerResearch #PrecisionMedicine #MedicalImaging #MachineLearning #DeepLearning #ComputerVision

✨ Exciting News! ✨ I'm thrilled to share that our latest research article has been published in the prestigious journal Cell Reports Medicine! 🧬📚 Our study employed advanced techniques - spatially transcriptomics, quantitative mass spectrometry-based proteomics, and multiplex immunofluorescence to explore the tumor microenvironment (TME) of metastatic SCLC. We profiled SCLC tissue sections generating transcriptomes from 72 regions across 10 SCLC tumors. (Clinicaltrials.gov identifier: NCT01851395) Key insights include: Cancer-Associated Fibroblasts (CAFs): Identified as a pivotal component contributing to TME heterogeneity, immune exclusion, and poor prognosis. TME-Driven Reprogramming: Substantial variation in non-malignant cells within the TME mirrors the tumor NE state, indicating dynamic TME-driven reprogramming. FGF Signaling: TME-derived FGF signaling directs SCLC towards a non-NE cell state, underscoring its role in tumor plasticity and chemoresistance. This work highlights the critical role of TME in shaping SCLC phenotypes and opens new avenues for targeted therapeutic strategies. Our findings emphasize the potential of modulating TME-tumor interactions to improve SCLC treatment outcomes. I am grateful for the collaboration and support from my colleagues and the broader research community. Together, we continue to advance our understanding of cancer biology. Read the full article here: https://lnkd.in/e_Yr2X6m #CancerResearch #SCLC #TumorMicroenvironment #CellReportsMedicine #ScientificResearch #LungCancer #Proteomics #Transcriptomics # SpatialTranscriptomics

Approaching the performance of macrophages in clinical trials from an engineering perspective, researchers from the Harvard John A. Paulson School of Engineering and Applied Sciences observed a correlation between shape-shifting abilities and transport efficiency, such that the better the macrophage was at shape shifting, the better able they were to get to the tumor, and found that a specific phenotype of macrophage was better at traveling to the tumor than others. "There is tremendous potential in utilizing macrophages to mediate anti-tumor immune responses in human tumors and clinical trials are ongoing to treat patients with macrophages,” says study co-author Dr. Guerriero of Brigham and Women's Hospital. “We learned in this study that, surprisingly, macrophages that resemble an M0 phenotype were most efficient at getting to their target. These data will have an immediate impact on clinical trials are likely to transform the next generation of macrophage-mediated therapies.” Read more: https://bit.ly/48m7pjZ #CancerResearch #Macrophage #ClinicalTrials