A 10-year follow-up study of nearly 2,500 U.S. men who received prostate cancer treatment will help inform decision-making in terms of treatments and side effects for a diverse population.
A study examined the rates of active surveillance use and evaluated the factors associated with selecting this management strategy over surgery or radiation in low-risk prostate cancer, with a focus on underserved Black patients who have been underrepresented in prior studies.
The NEST-1 study, which is evaluating botensilimab and balstilimab (BOT/BAL) in the neoadjuvant setting for colorectal cancer, both those with Microsatellite Stable (MSS) CRC and Microsatellite Instability High CRC (MSI-High), has demonstrated positive results.
The current standard of care for identifying targetable mutations in cancer treatment is to conduct molecular profiles on tumor tissue samples, but a study published in JAMA Network Open indicates that adding liquid biopsy testing for circulating tumor DNA mutations increases targetable mutation detection rates.
Fred Hutchinson Cancer Center researchers, led by Jonathan Bricker, launched an AI-powered chatbot app called QuitBot to help more people successfully quit smoking cigarettes.
Doctors at the University of New Mexico Comprehensive Cancer Center successfully treated blood cancer patients using allogeneic stem cell transplant—a first for New Mexico.
A study led by researchers from the UCLA Health Jonsson Comprehensive Cancer Center showed that using high doses of radiation while integrating an ablative radiotherapy technique called stereotactic ablative radiotherapy concurrently with chemotherapy is safe and effective in treating people with locally advanced non-small cell lung cancer that is not suitable for surgery.
Scientists at University of California San Diego School of Medicine used a machine learning algorithm to predict when cancer will resist chemotherapy.
Data published in The Journal for ImmunoTherapy of Cancer show ClearNote Health’s epigenomic platform may provide a novel tissue-free, liquid biopsy-based approach for prediction and monitoring of immunotherapy response for non-small cell lung cancer patients.
Researchers at Baylor College of Medicine and collaborating institutions developed a kinase inhibitor pulldown assay that can optimally enrich and quantify the small amounts of kinases present in biopsy samples in combination with mass-spectrometry techniques.