Cure.’s Post

“The researchers then performed extensive genomic profiling using advanced sequencing techniques, allowing them to identify recurrent genomic features and mutations associated with the disease. The result was the individualized risk model in multiple myeloma or IRMMa. The predictive model uses advanced statistical methodologies such as deep neural networks to generate individualized overall survival and event-free survival predictions for multiple myeloma patients. Rigorous validation of the IRMMa model using independent datasets was performed to ensure its accuracy and reliability in diverse patient populations. Additionally, the researchers analyzed treatment outcomes and variance among different therapeutic regimens, aiming to identify optimal treatment approaches tailored to individual patient characteristics. “- for such an awful cancer that impact the elderly as well as some below the age 50, its great to see work done to tailor treatment for the disease especially as this cancer can be chemo and radiotherapy resistant! #targetedtherapy #cancerresearch #multiplemyeloma #bloodcancer #interesting

“Our preclinical studies showed these immune cells to be particularly remarkable in targeting and completely eliminating the growth of the tumors," Matosevic said. "We found that we can engineer these cells at doses suitable for clinical use in humans. "This is significant because one of the major hurdles to clinical translation of cell-based therapies to humans has been the poor expansion and lack of potency of cells that were sourced directly from patients. Using an off-the-shelf, fully synthetic approach breaks down significant barriers to the manufacturing of these cells." #geneticengineering #cancer #braincancer #giloblastoma #stemcells #immunecells

✅This photo shows a beautiful #mitoticfigure in a malignant cancer cell. ✅Histopathology uses #mitoticfigures to diagnose tumors and assess their aggressiveness. These figures guide treatment decisions and predict prognosis. Standardizing counting methods and using ancillary techniques enhance accuracy. #pathology #mitoticfigures

“To discover the pathway cancer cells use to infiltrate the brain, researchers used large-scale gene editing technology to compare gene dependencies in glioblastoma when it was initially diagnosed and after it returned following standard treatments. By doing this, researchers discovered a new pathway used for axonal guidance—a signaling axis that helps establish normal brain architecture—that can become overrun by cancer cells. "In glioblastoma, we believe that the tumor hijacks this signaling pathway and uses it to invade and infiltrate the brain," says co-senior author Sheila Singh, professor with McMaster's Department of Surgery and director of the Center for Discovery in Cancer Research. The research was also co-led by Jason Moffat, head of the Genetics and Genome Biology program at The Hospital for Sick Children (SickKids). "If we can block this pathway, the hope is that we can block the invasive spread of glioblastoma and kill tumor cells that cannot be removed surgically," says Singh.” #braincancer #glioblastoma #cancer #cancerresearch #cancertreatment

✨ November marks 𝗟𝘂𝗻𝗴 𝗖𝗮𝗻𝗰𝗲𝗿 𝗔𝘄𝗮𝗿𝗲𝗻𝗲𝘀𝘀 𝗠𝗼𝗻𝘁𝗵. Did you know inherited mutations in the 𝘌𝘎𝘍𝘙 gene can increase the risk for lung cancer? We encourage you to share this post to promote awareness, early detection, and preventive measures. #ICARE #InheritedCancerRegistry #InheritedCancer #HereditaryCancer #Cancer #LungCancer #EGFR #CancerRisks #CancerGenetics #GeneticTesting #CancerPrevention #CancerAwareness #LungCancerAwareness #LungCancerAwarenessMonth Vanderbilt University Medical Center American Cancer Society American Society of Clinical Oncology (ASCO) ACMG - American College of Medical Genetics and Genomics

Comprehensive Overview of Genomic Alterations and Influencing Factors in IBD-Associated Colorectal Cancer

Prostate cancer in Western Kenya: Standards and Practice, Patients clinical identifications, Radio imaging and Biomarkers utility.

A bioinformatic analysis of secretome biomarkers of Glioblastoma multiform (GBM), brain cancer,

Machine-learning model predicts lung and liver cancer through genome sequence changes - LabPulse: Machine-learning model predicts lung and liver cancer through genome sequence changes  LabPulse http://dlvr.it/T48xCm #ai #artificialintelligence