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Full-Text Articles in Medicine and Health Sciences
Steap1-4 (Six-Transmembrane Epithelial Antigen Of The Prostate 1-4) And Their Clinical Implications For Prostate Cancer, Michael Xu, Latese Evans, Candice L Bizzaro, Fabio Quaglia, Cecilia E Verrillo, Li Li, Julia Stieglmaier, M J Schiewer, Lucia R Languino, William Kevin Kelly
Steap1-4 (Six-Transmembrane Epithelial Antigen Of The Prostate 1-4) And Their Clinical Implications For Prostate Cancer, Michael Xu, Latese Evans, Candice L Bizzaro, Fabio Quaglia, Cecilia E Verrillo, Li Li, Julia Stieglmaier, M J Schiewer, Lucia R Languino, William Kevin Kelly
Department of Urology Faculty Papers
Six-Transmembrane Epithelial Antigen of the Prostate 1-4 (STEAP1-4) compose a family of metalloproteinases involved in iron and copper homeostasis and other cellular processes. Thus far, five homologs are known: STEAP1, STEAP1B, STEAP2, STEAP3, and STEAP4. In prostate cancer, STEAP1, STEAP2, and STEAP4 are overexpressed, while STEAP3 expression is downregulated. Although the metalloreductase activities of STEAP1-4 are well documented, their other biological functions are not. Furthermore, the properties and expression levels of STEAP heterotrimers, homotrimers, heterodimers, and homodimers are not well understood. Nevertheless, studies over the last few decades have provided sufficient impetus to investigate STEAP1-4 as potential biomarkers and therapeutic …
Artificial Intelligence In The Radiomic Analysis Of Glioblastomas: A Review, Taxonomy, And Perspective, Ming Zhu, Sijia Li, Yu Kuang, Virigina B. Hill, Amy B. Heimberger, Lijie Zhai, Shenjie Zhai
Artificial Intelligence In The Radiomic Analysis Of Glioblastomas: A Review, Taxonomy, And Perspective, Ming Zhu, Sijia Li, Yu Kuang, Virigina B. Hill, Amy B. Heimberger, Lijie Zhai, Shenjie Zhai
Electrical & Computer Engineering Faculty Research
Radiological imaging techniques, including magnetic resonance imaging (MRI) and positron emission tomography (PET), are the standard-of-care non-invasive diagnostic approaches widely applied in neuro-oncology. Unfortunately, accurate interpretation of radiological imaging data is constantly challenged by the indistinguishable radiological image features shared by different pathological changes associated with tumor progression and/or various therapeutic interventions. In recent years, machine learning (ML)-based artificial intelligence (AI) technology has been widely applied in medical image processing and bioinformatics due to its advantages in implicit image feature extraction and integrative data analysis. Despite its recent rapid development, ML technology still faces many hurdles for its broader applications …
A Bayesian Phase I/Ii Biomarker-Based Design For Identifying Subgroup-Specific Optimal Dose For Immunotherapy, Beibei Guo, Yong Zang
A Bayesian Phase I/Ii Biomarker-Based Design For Identifying Subgroup-Specific Optimal Dose For Immunotherapy, Beibei Guo, Yong Zang
Faculty Publications
Immunotherapy is an innovative treatment that enlists the patient's immune system to battle tumors. The optimal dose for treating patients with an immunotherapeutic agent may differ according to their biomarker status. In this article, we propose a biomarker-based phase I/II dose-finding design for identifying subgroup-specific optimal dose for immunotherapy (BSOI) that jointly models the immune response, toxicity, and efficacy outcomes. We propose parsimonious yet flexible models to borrow information across different types of outcomes and subgroups. We quantify the desirability of the dose using a utility function and adopt a two-stage dose-finding algorithm to find the optimal dose for each …
Targeting Gastrointestinal Cancers With Chimeric Antigen Receptor (Car)-T Cell Therapy, Ross E Staudt, Robert D Carlson, Adam E. Snook
Targeting Gastrointestinal Cancers With Chimeric Antigen Receptor (Car)-T Cell Therapy, Ross E Staudt, Robert D Carlson, Adam E. Snook
Department of Pharmacology and Experimental Therapeutics Faculty Papers
The immune system is capable of remarkably potent and specific efficacy against infectious diseases. For decades, investigators sought to leverage those characteristics to create immune-based therapies (immunotherapy) that might be far more effective and less toxic than conventional chemotherapy and radiation therapy for cancer. Those studies revealed many factors and mechanisms underlying the success or failure of cancer immunotherapy, leading to synthetic biology approaches, including CAR-T cell therapy. In this approach, patient T cells are genetically modified to express a chimeric antigen receptor (CAR) that converts T cells of any specificity into tumor-specific T cells that can be expanded to …
Predicting Cancer Immunotherapy Response From Gut Microbiomes Using Machine Learning Models, Hai Liang, Jay-Hyun Jo, Zhiwei Zhang, Margaret A Macgibeny, Jungmin Han, Diana M Proctor, Monica E Taylor, You Che, Paul Juneau, Andrea B Apolo, John A Mcculloch, Diwakar Davar, Hassane M Zarour, Amiran K Dzutsev, Isaac Brownell, Giorgio Trinchieri, James L Gulley, Heidi H Kong
Predicting Cancer Immunotherapy Response From Gut Microbiomes Using Machine Learning Models, Hai Liang, Jay-Hyun Jo, Zhiwei Zhang, Margaret A Macgibeny, Jungmin Han, Diana M Proctor, Monica E Taylor, You Che, Paul Juneau, Andrea B Apolo, John A Mcculloch, Diwakar Davar, Hassane M Zarour, Amiran K Dzutsev, Isaac Brownell, Giorgio Trinchieri, James L Gulley, Heidi H Kong
Journal Articles
Cancer immunotherapy has significantly improved patient survival. Yet, half of patients do not respond to immunotherapy. Gut microbiomes have been linked to clinical responsiveness of melanoma patients on immunotherapies; however, different taxa have been associated with response status with implicated taxa inconsistent between studies. We used a tumor-agnostic approach to find common gut microbiome features of response among immunotherapy patients with different advanced stage cancers. A combined meta-analysis of 16S rRNA gene sequencing data from our mixed tumor cohort and three published immunotherapy gut microbiome datasets from different melanoma patient cohorts found certain gut bacterial taxa correlated with immunotherapy response …
Alternative Adenosine Receptor Activation: The Netrin-Adora2b Link., Xiaoyi Yuan, Tingting Mills, Marie-Francoise Doursout, Scott E Evans, Marcos F Vidal Melo, Holger K Eltzschig
Alternative Adenosine Receptor Activation: The Netrin-Adora2b Link., Xiaoyi Yuan, Tingting Mills, Marie-Francoise Doursout, Scott E Evans, Marcos F Vidal Melo, Holger K Eltzschig
Journal Articles
During hypoxia or inflammation, extracellular adenosine levels are elevated. Studies using pharmacologic approaches or genetic animal models pertinent to extracellular adenosine signaling implicate this pathway in attenuating hypoxia-associated inflammation. There are four distinct adenosine receptors. Of these, it is not surprising that the Adora2b adenosine receptor functions as an endogenous feedback loop to control hypoxia-associated inflammation. First, Adora2b activation requires higher adenosine concentrations compared to other adenosine receptors, similar to those achieved during hypoxic inflammation. Second, Adora2b is transcriptionally induced during hypoxia or inflammation by hypoxia-inducible transcription factor HIF1A. Studies seeking an alternative adenosine receptor activation mechanism have linked netrin-1 …