GeoMx® Cancer Transcriptome Atlas
Helping Your Research
The GeoMx® Cancer Transcriptome Atlas (CTA) is designed for comprehensive profiling of tumor biology, the tumor microenvironment, and the immune response. Profile RNA expression of over 1,800 genes simultaneously with spatial resolution from distinct regions of interest with a single tissue section using the GeoMx Digital Spatial Profiler.
The GeoMx CTA is designed to profile all aspects of tumor and tumor microenvironment biology
- Profile the global immune response
- Assess microenvironment immune activity
- Quantify tumor reactivity to the immune response and therapeutic treatments
- Measure clinically-derived gene sets including the 18-gene Tumor Inflammation Signature (TIS) known to be associated with response to PD-1/PD-L1 inhibitor pathway blockade, and the 50-gene Prediction Analysis of Microarray 50 signature (PAM50) known to be associated with breast cancer metastasis.
Publications
Opposing immune and genetic mechanisms shape oncogenic programs in synovial sarcoma
Synovial sarcoma (SyS) is an aggressive neoplasm driven by the SS18-SSX fusion, and is characterized by low T cell infiltration. Here, we studied the cancer-immune interplay in SyS using an integrative approach that combines single-cell RNA sequencing (scRNA-seq), spatial profiling and genetic and pharmacological perturbations.
The spatial landscape of lung pathology during COVID-19 progression
Recent studies have provided insights into the pathology and immune response to coronavirus disease 2019 (COVID-19)1–8. However, thorough interrogation of the interplay between infected cells and the immune system at sites of infection is lacking.
Temporal and spatial heterogeneity of host response to SARS-CoV-2 pulmonary infection
The relationship of SARS-CoV-2 pulmonary infection and severity of disease is not fully understood. Here we show analysis of autopsy specimens from 24 patients who succumbed to SARS-CoV-2 infection using a combination of different RNA and protein analytical platforms to characterize inter-patient and intra-patient heterogeneity of pulmonary virus infection.
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