Researchers at Kyushu University have developed and validated a machine-learning model that can accurately evaluate the density of surviving tumor cells after treatment in pathological images of osteosarcoma—the most prevalent malignant bone tumor. The model can assess how individual tumor cells respond to treatment and can predict overall patient prognosis more reliably than conventional methods.
Surgery and chemotherapy have significantly improved the outcomes of patients with localized osteosarcoma. However, patients with advanced metastatic disease (the stage where cancerous cells have spread to distant tissues) have a low survival rate. After a standard treatment of surgery and chemotherapy, assessing the prognosis of patients is essential for determining their subsequent individual treatment plans. However, predicting patient outcomes has many challenges.
Currently, prognosis relies on necrosis rate assessment, which involves pathologists evaluating the proportion of dead tissue within a tumor. Unfortunately, these methods are limited by variability between pathologists' assessments and may not accurately predict treatment response.
Annual prostate cancer cases worldwide are projected to double by the year 2040, and annual deaths are projected to increase by 85% to almost 700,000 over the same timeframe—mainly among men in low- and middle-income countries. A commissioned report published in The Lancet highlights the future landscape of prostate cancer and seeks to guide cancer experts worldwide on how to manage the massive influx of prostate cancer patients projected over the next two decades.
Brandon Mahal, M.D., radiation oncologist and translational epidemiologist at Sylvester Comprehensive Cancer Center at the University of Miami Miller School of Medicine, was a member of a group of international experts commissioned to write the collaborative article.
"Unlike a typical study, which describes a single or set of experiments, commissioned pieces involve The Lancet editors working with academic partners to address the most pressing issues in science, medicine and global health," Mahal explained.
He said the report was conceived back in 2020, when the journal's editors sought advice from a select group of 40 cancer experts to highlight the increasing burden of prostate cancer, with global cases projected to more than double by 2040.
"Specifically, they wanted our collective, international perspective on this looming global burden," Mahal said. "They asked us to report the extent of the problem, identify the most at-risk populations and explain how best to address the expected surge."
Besides outlining the scope of the problem—worldwide cases are expected to explode from 1.4 million now to 2.9 million in just 16 years—The Lancet report highlights both ethnic and geographic disparities in the overall burden of prostate cancer and emphasizes the need for more research into the factors driving these differences.
A nanosized polymer, developed by a research team from Ben-Gurion University of the Negev, can selectively deliver chemotherapeutic drugs to blood vessels that feed tumors and metastases and has emerged as an effective treatment for advanced cancer. The polymer eliminates colorectal cancer liver metastases and prolongs mice survival after a single dose therapy.
Colorectal cancer (CRC) is the third most diagnosed cancer and the third most common cause of cancer-related death in both men and women in the United States. The liver is the most common site for CRC metastasis, with around 70% of patients ultimately developing liver metastases.
Treatment options for metastatic disease are scarce, and while surgery remains the gold standard, many patients need additional therapies (chemotherapy, targeted, or immune therapy) for a curative-intended treatment.
Targeted therapies and immunotherapies directed against specific features of the tumor have emerged as promising therapeutic strategies for cancer patients, but their efficacy is often limited by the large variety of mutation profiles of CRC tumors, many of them conferring resistance to specific treatments.
Researchers have developed a functional precision medicine approach that targets cancer by combining genetic testing with a new way to test individual drugs on tumor samples. The results of the clinical study were published in Nature Medicine.
This combined approach, developed by Florida International University cancer researcher Diana Azzam, was used successfully for the first time to guide treatment of relapsed pediatric cancer patients in collaboration with First Ascent Biomedical and Dr. Maggie Fader at the Helen & Jacob Shaham Cancer & Blood Disorders Institute at Nicklaus Children's Hospital in Miami.
A new study led by researchers at Stanford Medicine finds that computer algorithms powered by artificial intelligence based on deep learning can help health care practitioners to diagnose skin cancers more accurately. Even dermatologists benefit from AI guidance, although their improvement is less than that seen for non-dermatologists.
"This is a clear demonstration of how AI can be used in collaboration with a physician to improve patient care," said professor of dermatology and of epidemiology Eleni Linos, MD. Linos leads the Stanford Center for Digital Health, which was launched to tackle some of the most pressing research questions at the intersection of technology and health by promoting collaboration between engineering, computer science, medicine and the humanities.
