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UVA Researcher Receives $2.4M for MPN Progression Study
by David Wallace The National Institutes of Health (NIH) has awarded a $2.4 million grant to Dr. Golam Mohi, a professor in the Department of Biochemistry and Molecular Genetics at the University of Virginia, to advance understanding of a group of blood cancers known as myeloproliferative neoplasms (MPNs). The research project, titled “Molecular Basis for […]
PV Remission to Recovery: Overcoming Life’s Challenges
by David Wallace A New Year, a New Perspective As 2025 begins, I’ve been reflecting on the unpredictable journey of aging—a path that’s less about smooth sailing and more about navigating challenges. After four years living in remission from polycythemia vera (PV), I’ve come to understand that maintaining good health requires resilience to overcome challenges […]
A Promising Drug for Breast Cancer Shows Potential to Treat MPN Blood Cancers
by David Wallace Researchers have discovered a new therapeutic avenue targeting a protein called RSK1 (ribosomal protein S6 kinase A1), which could revolutionize treatment for blood cancers such as Myeloproliferative Neoplasms (MPN) and secondary Acute Myeloid Leukemia (sAML). This protein plays a crucial role in driving cancer progression and inflammation. The Drug’s Mechanism The investigational […]
How Does Polycythemia Vera Differ from Polycythemia?
by David Wallace Polycythemia: A Comprehensive Overview Polycythemia is defined as having an abnormally high number of red blood cells in the blood—derived from the Latin “poly” (many), “cyte” (cell), and “hemo” (blood). This general term encompasses various conditions leading to this hematological abnormality. Polycythemia Vera (PV) fits under this umbrella but has its own […]
New Scoring Model Improves Prediction of Outcomes in Essential Thrombocythemia
by David Wallace Summary: Researchers have developed a new Essential Thrombocythemia scoring system called the “triple A” (AAA) model to predict outcomes in patients with essential thrombocythemia (ET), a type of blood cancer. This model uses three simple factors: age, absolute neutrophil count, and absolute lymphocyte count to categorize patients into different risk groups. The […]
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