Philadelphia, February 19, 2025 – Researchers have demonstrated the feasibility of a morphological-based approach to interpreting spatial transcriptomic (ST) data, helping to improve understanding of the lesions that occur in chronic kidney disease (CKD), at both the cellular and molecular levels. A recent study in The American Journal of Pathology , published by Elsevier, details how this new method could lead to the identification of new biomarkers and therapeutic strategies for patients.
ST technologies are a rapidly developing new tool for measuring RNA in their original spatial context, giving a molecular mechanistic dimension to tissue morphology. The application of ST technologies has already yielded important insights across many different tissues and disease models. By combining profiling of gene expression patterns with the spatial information of cells in tissues, ST provides a more complete understanding of the molecular and cellular organization of tissues and lesions.
Lead investigator Benjamin D. Humphreys, MD, PhD, Division of Nephrology, Department of Medicine, and the Department of Developmental Biology, Washington University in St. Louis, explains , "During ST data analysis, computationally-annotated clusters are often superimposed on a histological image. However, tissue morphology by standard light microscopic pathologic evaluation is not considered. This may preclude assimilation of important information that can help interpret the ST data. The kidney is a particularly heterogeneous organ in morphologic terms, with a high degree of spatial and temporal lesion variability often present in pathologic situations. We conducted a histopathological-based analysis of spatial transcriptomics on four human kidney samples with CKD, corresponding as closely as possible to how a kidney biopsy is interpreted in clinical practice."
The study demonstrates how:
Lead author Pierre Isnard, MD, PhD, Division of Nephrology, Department of Medicine, and the Department of Developmental Biology, Washington University in St. Louis, concludes, "ST technologies are new and increasingly used in the life sciences, but there is a lack of studies showing their benefits and applications. Here, we demonstrate the complementary nature of these technologies to standard morphological analysis of tissue for identifying, classifying, and understanding lesions. The value of these technologies in healthcare remains to be demonstrated. However, these methods provide a better understanding of the cellular and molecular mechanisms of diseases, which may help identify new biomarkers and/or therapeutic strategies for patients. "
American Journal Of Pathology
Experimental study
Cells
Histopathologic Analysis of Human Kidney Spatial Transcriptomics Data: Toward Precision Pathology