Oncotarget

Exploring the protein-based risk model for esophageal cancer recurrence, researchers identify biomarkers to improve treatment outcomes. Four prognostic molecular signatures show promise in predicting disease recurrence and stratifying patients based on risk levels.

New research paper explores targeting Krebs-cycle-deficient renal cell carcinoma with PARP inhibitors and low-dose alkylating chemo. Loss-of-function mutations in FH and SDH genes induce cancer syndromes. Fumarate and succinate inhibit DNA repair pathway, leading to accumulation of DNA double-strand breaks. Researchers develop murine models demonstrating alterations in transcriptomic and methylation profile.

Dr. Balraj Singh, a researcher from The University of Texas MD Anderson Cancer Center, discusses inhibiting resistant triple-negative breast cancer cells with low-dose 6-mercaptopurine and 5-azacitidine. They explore the efficacy of these drugs and their potential to overcome chemotherapy resistance. The podcast also delves into the use of 6MP in enhancing immune checkpoint blockage for combating autoimmunity and cancer cells.

Researchers from St. Jude Children’s Research Hospital discuss the challenges of treating SHH-Medulloblastoma in young children through standard methods such as radiation therapy and SMO inhibitors. They highlight the need for novel therapeutic approaches and explore the potential of an ABC transporter as a new target for treatment.

Researchers Dr. Glenn Simmons Jr. and Dr. Stefani Thomas discuss targeting lipid metabolism in ovarian cancer treatment. They highlight the role of unsaturated fatty acids in cancer cell growth, chemotherapy resistance, and immune response evasion. The podcast explores challenges in current therapies and the use of mass spectrometry to identify potential targets for more effective treatments.

Discover the development of a targeted imaging probe for detecting bladder cancer using polypeptide fusion proteins. Learn about the high sensitivity and selectivity of a NIR probe in labeling tumor tissue, showcasing potential for clinical translation and patient imaging.

Exploring how machine learning is used to predict immunotherapy response with a focus on gut microbiomes. Studying the impact of gut microbiomes on the immune system and their potential as a biomarker. Analyzing the predictive potential of gut microbiomes in immunotherapy response and the significance of machine learning in understanding microbiome-immunotherapy interactions.

Exploring the synergistic effects of epigenetic and immunotherapy treatments in managing aggressive blastic mantle cell lymphoma, a challenging subtype of non-Hodgkin’s lymphoma, with high recurrence rates and poor treatment outcomes. Researchers discuss potential breakthroughs in offering improved survival rates and long-term remissions through a combination of treatment modalities, paving the way for future research on predictive biomarkers.

Discussing the significance of kinase activity in renal cell carcinoma and the response to tyrosine kinase inhibitors, focusing on the challenges of identifying biomarkers for treatment selection and the potential of PTK profiling for personalized therapies.

Exploring the association of GPC3 with poor outcomes in MCPyV-negative Merkel cell carcinoma, researchers investigate its link to patient survival and tumor characteristics. The high prevalence of GPC3 expression in MCC tumors, especially in MCPyV negative cases, correlates with increased mortality risk, making it a promising target for drug therapy in MCC.