Targeting histone modifications in colorectal cancer: therapeutic potential of epigenetic modifiers on acetylation, methylation and phosphorylation
Peer-Reviewed Publication
Updates every hour. Last Updated: 23-Jun-2026 04:16 ET (23-Jun-2026 08:16 GMT/UTC)
Home testing kits that screen for cervical cancer risk could be a game-changer for reducing health inequalities for physically Disabled women, according to a new University of Sheffield study revealing that over 50% would prefer a self-test over a traditional clinic visit.
Researchers from the Technion – Israel Institute of Technology, in collaboration with international partners, have developed an artificial intelligence (AI) model that predicts both the risk of breast cancer recurrence and the likelihood of benefit from chemotherapy using standard pathology slides. The study, published in The Lancet Oncology and presented at ESMO, is the first to validate such a model using data from a large randomized clinical trial (TAILORx).
The AI system analyzes high-resolution digital images of tumor tissue and identifies complex visual patterns linked to cancer behavior and treatment response. It generates a score within minutes, offering a fast, low-cost, and widely accessible alternative to genomic tests such as Oncotype DX, which are expensive and not globally available.
The model was validated on thousands of patients across multiple countries and healthcare systems, demonstrating consistent performance. By enabling more accurate treatment decisions, the approach could reduce unnecessary chemotherapy and expand access to personalized cancer care, particularly in low-resource settings.
Researchers are now working toward clinical implementation and further development, including expansion to additional cancer types and treatments.
The dedicator of cytokinesis 10 (DOCK10) gene has been identified as a key driver of abnormal insulin secretion in insulinomas, as reported by researchers from Institute of Science Tokyo. Using surgical specimens and patient-derived organoids, the team performed comprehensive genetic and transcriptomic analyses, revealing that inhibiting a DOCK10-related pathway reduced excessive insulin release in cellular and animal models. These results pave the way for novel diagnostic biomarkers and treatment options for insulinomas.
A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results predicted a patient’s risk of hepatocellular carcinoma (HCC), the most common type of liver cancer, with high accuracy.
In new research to be presented at this year’s European Congress on Obesity (ECO2026) in Istanbul, Turkey (12-15 May), a global panel of 21 obesity and cancer experts suggest that to test the potential efficacy of the new generation of obesity drugs such as semaglutide and tirzepatide in preventing obesity-related cancer (ORC), a trial of the drugs for some 5,000 participants at high risk of cancer due to their having a cancer pre-cursor condition will provide the required answers.