- Details
- Brandon Mahal discusses a large-scale, retrospective analysis involving nearly 12,000 patients, exploring comprehensive genomic profiling and treatment patterns in advanced prostate cancer across different ancestries. The study reveals significant variances in incidence and mortality by race and genomic ancestry, emphasizing a greater burden on men of African ancestry. It exposes how these men rec...
|
- Details
- Andrea Miyahira hosts Tamara Lotan to discuss the paper, "Predicting Prostate Cancer Molecular Subtype with Deep Learning on Histopathologic Images." Dr. Lotan details the collaborative work with Angelo De Marzo's lab at Johns Hopkins and AIRA MATRIX, an AI deep learning company in India. The study aims to predict underlying molecular subtypes of prostate cancer using deep learning algorithms on h...
|
- Details
- In this discussion, Andrea Miyahira speaks with Ping Mu about his group's paper. The research focuses on the role of SYNCRIP in controlling APOBEC-driven mutagenesis in prostate cancer. Dr. Mu explains that the loss of SYNCRIP leads to a break in the mechanism controlling this mutagenesis driver, resulting in prostate cancer gaining resistance to AR therapy. The conversation highlights the tumor h...
|
- Details
- Burcu Darst explores her team's study on developing polygenic risk scores for prostate cancer in men of African and European ancestry. This study aims at addressing health disparities, and uses a large, diverse prostate cancer GWAS involving over 230,000 men from various populations. The results indicate that men in the top polygenic risk score decile are three to four times more likely to have pr...
|
- Details
- Andrew Hsieh highlights his team's research on a new tumor suppressor mechanism termed transcriptional-translational conflict. The research primarily focuses on ARID1A, a component of the SWI/SNF chromatin remodeling complex, which is frequently deregulated in bladder cancer. In absence of ARID1A, up-regulated oncogenic gene networks were observed, but no tumorigenesis occurred due to a conflict b...
|
- Details
- Andrea Miyahira interviews John Lee about his team's publication in Nature Communications. Dr. Lee discusses the focus of their research on a protein called STEAP1, known to be enriched in prostate cancers and the target of substantial therapeutic development. He provides an overview of previous efforts, such as Genentech's discontinued ADC, and ongoing developments like Amgen's AMG 509. The resea...
|
- Details
- In a discussion hosted by Andrea Miyahira, David Quigley discusses his team's research on the genomic and epigenomic landscape of double-negative metastatic prostate cancer. Dr. Quigley provides insights into the mechanisms behind the disease's resistance to targeted therapy, highlighting the transformation of prostate adenocarcinoma cells towards either maintaining their original nature or transi...
|
- Details
- Hiten Patel talks about the significant role of the Veterans Health Administration in prostate cancer treatment and research. Dr. Patel outlines the formation of prostate cancer centers of excellence within the VA, intended to coordinate efforts to improve oncology care and survival rates for veterans. The Precision Oncology Program for the Cancer of the Prostate (POPCaP), created in partnership w...
|
- Details
- Veda Giri discusses the promising results of the TARGET study in an interview with Alicia Morgans. The study examined an innovative web-based approach to expand genetic testing access for prostate cancer patients. The study addressed the lack of sustainable patient-genetic counselor interaction by implementing a patient-driven web tool, which was proven to be non-inferior to traditional genetic co...
|
- Details
- Andrea Miyahira and Susan Halabi discuss Dr Halabi's prognostic model for overall survival in patients with metastatic castration-resistant prostate cancer. Originating in the early 2000s, the model sought to provide patients with more specific information about their prognoses and categorize them into different risk groups. Dr. Halabi's model comprises eight easily obtainable clinical variables,...
|
