Medical Bulletin 03/July/2023 - Video

Here are the top medical news for the day:

Researchers identify unique cell receptor, potential for new therapies

Researchers from the University of Colorado Anschutz Medical Campus have identified a potential new immune checkpoint receptor that could lead to treatments for diseases such as lung and bowel cancer and autoimmune conditions including IBD.

The study examines a family of 13 receptors or proteins that transmit signals for cells to follow, called killer cell immunoglobulin-like receptors (KIR). Of the 13 receptors, one is unique in that it has not readily been observed in the immune cells of peripheral blood. Researchers identified that this mysterious receptor, called KIR3DL3, is found in the intestine and lungs, suggesting it could provide signals specifically required by immune cells that are resident in mucosal tissues.

Researchers were able to determine the tissue distribution of the elusive KIR3DL3 receptor by searching for a sequence of nucleotides specific to KIR3DL3 in public RNA sequencing databases. After developing a short list of probable tissues where KIR3DL3 could be expressed, they collaborated with lab groups in the United Kingdom that created a KIR3DL3-specific antibody, and colleagues from the University of Colorado School of Medicine who supplied the tissues. Using this antibody, the researchers confirmed KIR3DL3 protein expression was rare in peripheral blood and most common in the intestine.

Reference:Billy Palmer et al,Science Immunology, the UNIVERSITY OF COLORADO ANSCHUTZ MEDICAL CAMPUS

Deep-learning chest radiograph model predicts community-acquired pneumonia mortality

According to an accepted manuscript published in ARRS’ own American Journal of Roentgenology (AJR), a deep learning-based model using initial chest radiographs predicted 30-day mortality in patients with community-acquired pneumonia (CAP), improving upon the performance of an established risk prediction tool.

In this AJR accepted manuscript, a DL model was developed in 7,105 patients via one institution from March 2013 to December 2019 (3:1:1 allocation to training, validation, and internal test sets) to predict risk of all-cause mortality within 30 days after CAP diagnosis using patients’ initial chest radiograph. Hwang et al. then evaluated their DL model in patients diagnosed with CAP during emergency department visits at the same institution as the development cohort from January 2020 to December 2020 [temporal test cohort (n = 947)], and from two additional different institutions [external test cohort A (n = 467), January 2020 to December 2020; external test cohort B (n = 381), March 2019 to October 2021]. AUCs were compared between the DL model and a risk score based on confusion, blood urea nitrogen level, respiratory rate, blood pressure, and age ≥ 65 years

Reference: A Deep-Learning Model Using Chest Radiographs for Prediction of 30-Day Mortality in Patients With Community-Acquired Pneumonia: Development and External Validation, American Journal of Roentgenology, DOI 10.2214/AJR.23.29414

New study validates the first-ever predictive AI biomarker of androgen deprivation therapy (ADT) benefit in prostate cancer

Data from a new study published in NEJM Evidence shows promise for personalized use of short-term ADT in men with predominantly intermediate-risk prostate cancer. The study involved ArteraAI, a developer of multimodal artificial intelligence-based predictive and prognostic cancer tests, and other researchers including those from University Hospitals (UH) Seidman Cancer Center. The information validates the first-ever predictive AI biomarker of androgen deprivation therapy (ADT) benefit in prostate cancer.

The study used novel deep learning methodology and histopathology image data from more than 5,000 patients across five Phase 3 randomized trials, with long-term follow-up. Patients in these trials were enrolled from over 100 centers across the US and Canada. The predictive AI biomarker was developed using datasets comprising about 20% African American patients. In past U.S.-based clinical trials, African American men have made up only 10.8% of prostate cancer trial participants.

Reference: Artificial Intelligence Predictive Model for Hormone Therapy Use in Prostate Cancer, NEJM Evidence, DOI 10.1056/EVIDoa2300023