nRichDX’s Post

#SpeakingofScience: Could there be a link between gut microbes and #cancertreatment outcomes? According to recent studies, the answer is yes—despite methodological challenges. Debates over tumor #microbiomes underscore the complexities of understanding their role in #cancer, and ongoing exploration promises breakthroughs in cancer #biology. Check out this Medscape article for more transformative insights in the #cancerresearch field, driven by incredible institutions such as the Cedars-Sinai Medical Center and Johns Hopkins Medicine! 🔬#cancerawareness #biotech #medicalresearch #clinicalresearch #medtech #medicalinnovation #medicalscience https://lnkd.in/e7w7a5nw

An AI-driven method called MRD-EDGE predicts cancer recurrence with high sensitivity by detecting tumor DNA in blood. Developed by a team from Weill Cornell Medicine and other institutions, this machine-learning model identifies cancer-specific patterns in DNA sequencing data, enabling detection of cancer recurrence months or years earlier than standard methods. Click here to read more: https://bit.ly/3z4PrGj #artificalintelligence #MRD #liquidbiopsy #venturecapital #privateequity #deerbornedifference

🧬 The EMBER approach is transforming how to understand and interpret breast cancer at the molecular level. By creating a unified space of 11,000 transcriptomes, EMBER not only refines diagnosis but also enhances our ability to predict clinical responses to therapies. This breakthrough signifies a leap towards personalized medicine, where treatments are tailored to individual genetic profiles. It's a step closer to making RNA-seq a standard in diagnostics, potentially replacing traditional methods for a more precise approach p/b École polytechnique fédérale de Lausanne, EPFL, The Institute of Cancer Research, Carlos Ronchi, Syed Haider, Cathrin Brisken, MD PhD #BiomedicalInnovation #PersonalizedMedicine #BreastCancerResearch https://lnkd.in/gdYPhnDg

An AI-driven method called MRD-EDGE predicts cancer recurrence with high sensitivity by detecting tumor DNA in blood. Developed by a team from Weill Cornell Medicine and other institutions, this machine-learning model identifies cancer-specific patterns in DNA sequencing data, enabling detection of cancer recurrence months or years earlier than standard methods. Click here to read more: https://bit.ly/3z4PrGj #artificalintelligence #MRD #liquidbiopsy #venturecapital #privateequity #deerbornedifference

New immunosuppressive mechanism in brain cancer Until now, it has been poorly understood how monocyte-derived macrophages and microglia create an immunosuppressive tumor microenvironment in glioblastoma. The lab investigated the cellular “how” of glioblastoma immunosuppression and identified that, as glioblastoma progressed, monocyte-derived macrophages came to outnumber microglia — which indicated that monocyte-derived macrophages’ eventuality to becoming the majority in the tumor microenvironment was advantageous to the cancer’s goal of evading immune response. Indeed, monocyte-derived macrophages, but not microglia, blocked the activity of T cells (immune cells that destroy tumor cells), in preclinical models and patients. The team confirmed this finding when they assessed preclinical models of glioblastoma with artificially reduced numbers of monocyte-derived macrophages. And as the group expected, the models with fewer malicious macrophages in the tumor microenvironment showed improved outcomes relative to the standard glioblastoma models. #ScienceMission #sciencenewshighlights https://lnkd.in/dHTTm7UD

#PaperoftheDay: "Exploring oncogenic driver molecular alterations in hispanic/latin american cancer patients: A call for enhanced molecular understanding" DOI ⬇️ https://lnkd.in/e3_GMgt3 #cancer #research #openaccess #peerreviewed #journalpublication #publishing

Compelling evidence shows that the frequency of T cells in the tumor microenvironment correlates with prognosis and the response to immunotherapy. However, considerable heterogeneity exists within tumor-infiltrating T cells, and the significance of their genomic and transcriptomic landscape on clinical outcomes remains to be elucidated p/b Shinshu University, Roswell Park Comprehensive Cancer Center, University of Southern California, Fumito Ito, MD, PhD, FACS #tumormicroenvironment #multiomics #immunooncology https://lnkd.in/gekFVKHu

Check out the pre-print of our comprehensive and "green" pipeline for Fast TILs estimation in lung cancer WSIs. The work is a result of a collaboration between the Translational Cancer Research Group and The Department of Computer Science at UiT. The pipeline achieved an AUC of 0.65 for disease-specific survival in our retrospective lung cancer cohort beating previous immune cell scores in in the same cohort (CD8 in TMA 0.59 and immune phenotypes 0.58). As reference TNM obtains AUC 0.66 in the same cohort. The pipeline comprise several steps culminating in TILs being estimated by a modified version of the HoVerNet architecture and will run on most recent GPUs. Further, the semi-stochastic patch sampling significantly reduces the number of patches going through the pipeline thus saving power and reducing CO2 emissions - resulting in green AI for digital pathology. In addition it is fully open-source and modular.

I am glad to share our short paper about genes and mutations that can be responsible for recurrence in young patients with oral cancer. https://lnkd.in/dTQS4cry #oralcancer #sequencing #mutation #EPOY

Dr. Arutha Kulasinghe, discusses the transformative role of #spatialbiology in #cancer research in an exclusive interview for #ONCOLife. By exploring the microenvironment of #tumors and identifying unique #biomarkers, his work aims to personalize #immunotherapy treatments, promising improved outcomes for patients by distinguishing between likely responders and non-responders to such therapies.  https://lnkd.in/dxukHN6T