From images to insights: Deep spatial phenotyping reveals disease and treatment biomarkers
This webcast presents the use of a 51-plex panel that covers a range of functional and tumor microenvironment-related biomarkers
Webinar
Part 1: PhenoCycler-Fusion: High-parameter Single-cell Spatial Biology
Learn about the power of comprehensive spatial phenotyping and its applications
Part 1: PhenoCycler-Fusion: High-parameter Single-cell Spatial Biology Read More »
PhenoImager Data Analysis Using QuPath and Python
In this webinar, Akoya Biosciences’ application scientists Aditya and Ning will present a framework for analyzing multiplex immunofluorescence images generated on the PhenoImager platform.
PhenoImager Data Analysis Using QuPath and Python Read More »
Tertiary Lymphoid Structures in Solid Tumours
During this webinar, Dr. Jessica Da Gama Duarte from Olivia Newton-John Cancer Research Institute will present the protocol for the in situ interrogation and characterization of TLSs in human and murine tissue sections using Opal-tyramide signal amplification multiplex immunohistochemistry.
Tertiary Lymphoid Structures in Solid Tumours Read More »
Transforming Biomarker Development for Cancer Immunotherapy: Introducing the PhenoCode Signature Approach
As cancer treatment evolves with the advent of new immunotherapies, it is crucial to accurately identify which patients will respond to these treatments. The tumor microenvironment (TME) has been shown to be a key factor in determining therapeutic responses across various cancer types.
PhenoImager Solutions: Bringing Speed and Scale to the Forefront of Multiplex Imaging and Spatial Phenotyping
Join Akoya Biosciences for a webinar on the PhenoImager Solution, which revolutionizes spatial phenotyping for translational and clinical research with a focus on speed, scale, accuracy, and reproducibility.
Developing a Spatio-Temporal Single-Cell Type Map of Adult Human Tissues
During this webinar, Dr. Cecilia Lindskog, research group leader and associate professor from Uppsala University, describes how scRNA-seq, spatial proteomics, and machine learning algorithms can be used to generate high-resolution spatio-temporal maps of human tissues.
Developing a Spatio-Temporal Single-Cell Type Map of Adult Human Tissues Read More »
The association between the tumor immune microenvironments and clinical outcome in low-grade, early-stage endometrial cancer patients
Endometrial cancer is the most common gynecologic malignancy diagnosed in western countries, with most cases diagnosed as low-grade, early-stage disease.
Understanding the immune landscape of non-muscle invasive bladder cancer (NMIBC) and its influence on BCG immunotherapy
Bladder cancer (BC) is the 10th most common cancer world-wide with an estimated 570,000+ people being diagnosed in 2020.
Rapid Development of Spatial Signatures as Predictive Biomarkers for Immunotherapy Response
The emergence of new immunotherapies as the first line of treatment for cancer, necessitates the development of clinically useful biomarkers to select responders that will be critical for the advancement of such treatments.
