American Cancer Society warns of increase in U.S. food swamps; no substantial progress reducing food deserts for millions of people
Peer-Reviewed Publication
Updates every hour. Last Updated: 22-Jun-2026 16:16 ET (22-Jun-2026 20:16 GMT/UTC)
Published today in Nature, researchers at the University of Pittsburgh School of Medicine and UPMC Hillman Cancer Center report a previously unrecognized change in how the cell’s genetic material is packaged into structures called chromosomes, that helps explain how some aggressive cancers sustain unlimited growth.
A research team has identified TATA box-binding protein-associated factor 1 (TAF1) as a molecular switch that helps determine whether cancer cells resist or undergo ferroptosis, a regulated form of cell death driven by lipid peroxide buildup.
Researchers at the Icahn School of Medicine at Mount Sinai have identified a previously hidden druggable site in a cancer-related protein that could open the door toward the development of a new generation of more precise cancer drugs. The finding also reveals important limitations in today’s artificial intelligence tools for drug discovery. The study, published in the June 2 online issue of the Journal of the American Chemical Society [10.1021/jacs.6c05178], focused on PKMYT1, a type of protein known as a kinase that helps control how cells grow and divide. Because this process can go wrong in cancer, PKMYT1 has emerged as a promising target for new cancer drugs.
In response to stress or damage, cells undergo senescence and stop dividing. However, if senescent cells accumulate in tissues over the long term, chronic inflammation occurs and the risk of cancer increases. Researchers at the German Cancer Research Center (DKFZ) have now discovered a previously unknown mechanism by which senescent cells protect themselves from oxidative stress and a specific form of cell death known as ferroptosis. In the long term, these findings could provide new avenues for cancer therapies and the treatment of age-related diseases.
Drug delivery and diagnostic imaging often lack specificity, but a new “TRACE” method lets specially‑caged compounds stay inert until a target cell’s enzymes quickly remove the cage, potentially allowing for more precise drug delivery and sharper diagnostic imaging.
A new study in Science Bulletin presents DVSTP, a deep learning system that integrates pathology images with spatial transcriptomics and proteomics to map intra-tumor heterogeneity. DVSTP predicts molecular profiles from routine pathology slides, making spatial multi-omics more accessible. Whole–tumor 3D reconstruction reveals that SRSF6 drives immune exclusion and is associated with poor clinical outcomes.