New research shows how AI may help avoid unnecessary chemotherapy for breast cancer patients
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Updates every hour. Last Updated: 23-Jun-2026 05:16 ET (23-Jun-2026 09:16 GMT/UTC)
Reported June 23 in Nature Biomedical Engineering, researchers at Vanderbilt Health and centers in Hong Kong have created a versatile uncertainty-aware AI framework broadly adaptable as a wrapper for digital pathology AI systems. (An AI wrapper acts as an interface layer that customizes, formats and automates how users interact with the underlying intelligence.) They demonstrate their wrapper, called TRUECAM, primarily with reference to non-small cell lung cancer (NSCLC) subtyping using whole-slide images.
A study published in PhotoniX Life presents a label-free method for mapping subcellular dynamics using wide-field interferometric scattering (iSCAT) microscopy and power spectral density (PSD) analysis. By fitting the pixel-wise PSD of iSCAT signals to an inverse-power-law relationship over 30–1,250 Hz, the researchers generated spectral exponent maps that visualize the characteristics and strength of subcellular motion. The method distinguished between mitotic and interphase cells, between live and apoptotic cells, and among thyroid cancer cell subtypes with increasing malignancy, highlighting a potential intrinsic optical marker for mechanobiology, cancer research, and stem cell assessment.
Salk Institute researchers investigated the impacts of entinostat, a drug that targets HDAC proteins, and found it inactivates DNA damage repair genes in pancreatic cancer cells. Their discovery led to new treatment strategies that pair entinostat with DNA-damaging therapies, as well as the development of a nanoparticle-based delivery approach that limits toxicity by selectively delivering entinostat to tumors. The findings could improve treatment outcomes and expand therapeutic options for pancreatic cancer, and similar strategies could be applied for treating other cancer types that resist DNA-damaging therapies.
A new study led by researchers at WashU Medicine suggests that younger generations are aging biologically faster than their older counterparts. This faster biological aging was also linked to early-onset cancers.