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Digital Oncology Insights: January 15 - January 21

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Patients now understand the risk numbers perfectly, yet anxiety still drives them to choose preventive surgery A new study examining genetic counseling reveals a complex gap between understanding statistics and making medical decisions. Researchers tested a visual aid designed to help breast cancer patients understand their specific risk of developing cancer in the opposite breast. While the tool successfully improved the patients accuracy in estimating their numerical risk it surprisingly had little impact on their actual choices. Many women still opted for preventive mastectomies driven by anxiety and a desire for symmetry rather than the medical data itself. This finding highlights that clinical decision making is deeply emotional and cannot be swayed by numbers alone. It suggests that future counseling tools must address psychological factors and personal fears just as much as they address statistical probabilities to truly support patients in making informed choices. Read the ...
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Scientists are using Lungs-on-Chips to simulate human tissue and prevent serious radiation-induced lung injury

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 Radiation therapy is a cornerstone of cancer treatment but it often causes severe collateral damage to the lungs known as radiation induced lung injury or RILI. To better understand and prevent this researchers are moving beyond animal models to use advanced lung on a chip technology. These microfluidic devices simulate the breathing motions and cellular structure of human lung tissue allowing scientists to observe exactly how radiation damages cells at a molecular level. The study is using these chips to test new therapies including antifibrotic drugs that could protect healthy lung tissue during cancer treatment. By providing a highly accurate model of human physiology this technology allows for the rapid screening of potential protective agents bringing us closer to a future where cancer can be irradiated without permanently scarring the patients lungs. Read the original article at: https://www.nature.com/articles/s41598-025-31582-1   Follow us on Instagram , Twit...
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Common drugs for cholesterol and migraines have been found to combine and kill aggressive childhood neuroblastoma

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 In a promising breakthrough for pediatric cancer researchers have used machine learning to identify a potent new treatment using drugs that are already on pharmacy shelves. The study focused on neuroblastoma a childhood cancer that is notoriously resistant to chemotherapy. By analyzing vast datasets of gene interactions the AI identified that combining statins used for cholesterol with phenothiazines used for migraines creates a deadly effect on tumor cells. This specific drug cocktail works by disrupting the cancer cells ability to manage lipids causing them to die while leaving healthy cells relatively unharmed. In mouse models this combination significantly slowed tumor growth and extended survival. This research highlights the immense potential of drug repurposing where artificial intelligence can uncover life saving uses for existing safe medications without the decade long timeline of developing new drugs from scratch. Read the original article at: https://medicalxpress.c...
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Treatment targets are failing. Systemic complexity is hiding the true, deadly length of cancer waiting times

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 A critical analysis of cancer care delivery argues that the current system of waiting time targets is outdated and dangerously misleading. The report warns that benchmarks such as the 62 day referral to treatment target are frequently missed and fail to capture the reality of modern complex care pathways. Patients who require multiple diagnostic tests or specialized scans often face delays that are invisible in the official data yet these delays significantly increase mortality risks. The authors contend that the increasing complexity of cancer cases combined with a lack of investment in staff and facilities has created a crisis that simple targets cannot fix. They call for a systemic overhaul involving a national learning system that uses real time data to identify bottlenecks and prioritize patients based on clinical urgency rather than arbitrary administrative clocks. Read the original article at: http://www.bmj.com/content/392/bmj.s14.short?rss=1 Follow us on Instagram , ...
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Patients now understand the risk numbers perfectly, yet anxiety still drives them to choose preventive surgery

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 A new study examining genetic counseling reveals a complex gap between understanding statistics and making medical decisions. Researchers tested a visual aid designed to help breast cancer patients understand their specific risk of developing cancer in the opposite breast. While the tool successfully improved the patients accuracy in estimating their numerical risk it surprisingly had little impact on their actual choices. Many women still opted for preventive mastectomies driven by anxiety and a desire for symmetry rather than the medical data itself. This finding highlights that clinical decision making is deeply emotional and cannot be swayed by numbers alone. It suggests that future counseling tools must address psychological factors and personal fears just as much as they address statistical probabilities to truly support patients in making informed choices. Read the original article at: https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2843738 Follow us on Ins...
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Digital Oncology Insights: January 8 - January 14

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  Mount Sinai’s new AI replaces weeks of manual review, scanning records in real-time to find trial patients instantly. A leading cancer center in New York has deployed a specialized artificial intelligence platform to solve the persistent problem of low enrollment in clinical trials. The system uses a large language model trained specifically on oncology data to scan electronic health records in real time. Unlike general AI tools this model understands complex cancer terminology including specific biomarkers and treatment histories hidden in unstructured doctor notes. By automating the screening process the technology identifies eligible patients the moment they qualify replacing the slow and fragmented manual review that often causes patients to miss out on experimental therapies. Clinicians report that the tool drastically reduces the administrative burden allowing them to focus on discussing meaningful treatment options with patients rather than sifting through paperwork. This ...
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CRISPR allows researchers to edit the genetic source code quicker and cheaper than ever before.

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 The gene editing tool CRISPR has fundamentally transformed cancer research by acting as molecular scissors that can cut and modify DNA with unprecedented ease. Since its introduction the technology has allowed scientists to deactivate specific genes or introduce new DNA sequences much faster and cheaper than older methods allowed. This efficiency is accelerating the development of next generation therapies including CAR T cells that are engineered to hunt down cancer more effectively. Researchers are currently using the tool to create more accurate mouse models of human cancer and to identify the genetic drivers of tumor growth. While challenges remain regarding how to deliver the tool safely into the human body without affecting healthy cells the technology offers a promising path toward treating cancer at its genetic root rather than just managing symptoms. Read the original article at: https://www.cancer.gov/news-events/cancer-currents-blog/2020/crispr-cancer-research-treatm...
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