A lab-designed molecule developed and extensively studied by scientists with Virginia Tech’s Fralin Biomedical Research Institute at VTC could represent a breakthrough in slowing tumor recurrence in glioblastoma, an aggressive and deadly form of brain cancer.

Carnegie Mellon University researchers have developed a new way to help doctors make better, personalized decisions and predict how a disease or treatment might play out in the future. Researchers from CMU’s School of Computer Science developed a new approach to bridge the gap between available data and actionable insight, creating personalized models to help doctors better understand individual patients and improve their prognosis. The researchers published their work in the Proceedings of the National Academy of Sciences. The team introduced contextualized modeling, a family of ultra-personalized machine learning methods, to build individualized gene network models for nearly 8,000 tumors across 25 cancer types simultaneously. These networks helped identify new cancer biology, revealing hidden cancer subtypes and improving survival predictions, especially for rare cancers. This development opens the door to more precise, individualized cancer treatment.

Researchers have identified C5aR1 as a novel biomarker for metastasis risk and poor prognosis in patients with cutaneous squamous cell carcinoma (cSCC), the most common type of metastatic skin cancer. The new study's findings in The American Journal of Pathology, published by Elsevier, found that C5aR1 promotes the invasion of cSCC tumor cells. Its elevated presence suggests that C5aR1 might serve as a useful prognostic marker for metastatic disease and, potentially, a target for future therapies in advanced cSCC.

Gliomas are among the deadliest brain tumors, with limited treatment options and poor survival rates. Scientists from China identified FAM111B, a DNA-repair-associated protein, as a key driver of glioma progression. The study shows that FAM111B overexpression enhances tumor growth and aggressiveness by activating the PI3K/AKT pathway. This is the first research to link FAM111B to gliomas, offering a promising new biomarker and therapeutic target for this intractable disease.

CAR T cell immunotherapy, which uses a patient’s own modified immune cells to find and destroy cancer cells, can produce dramatic results when treating blood cancers like lymphoma and leukemia and shows promise against solid tumors. Now researchers at Case Western Reserve University are developing a new device to harvest T cells that might make CAR T cell therapy less expensive and more widely available.

SAVANA uses a machine learning algorithm to identify cancer-specific structural variations and copy number aberrations in long-read DNA sequencing data.

The complex structure of cancer genomes means that standard analysis tools give false-positive results, leading to erroneous clinical interpretations of tumour biology. SAVANA significantly reduces such errors.

SAVANA offers rapid and reliable genomic analysis to better analyse clinical samples, thereby informing cancer diagnosis and therapeutic interventions.

Chondrosarcoma (CHS) is a rare and aggressive form of bone cancer characterized by its resistance to conventional therapies. The long non-coding RNA taurine up-regulated gene 1 (TUG1) has been reported to be implicated in various cancers; however, its role in CHS remains poorly understood.

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide. Given its rising global incidence, poor prognosis, high recurrence, and metastatic potential, there is an urgent need to investigate the underlying mechanisms driving tumorigenesis and progression to develop novel treatment strategies.