Year: 2024
Type: article
Abstract: The evolution of precision oncology has necessitated the integration of histopathological and genomic data to achieve greater diagnostic, prognostic, and therapeutic accuracy. Histopathology provides essential morphological insights into tumor architecture, cellular differentiation, and microenvironmental features, forming the diagnostic foundation in oncology. Genomic profiling complements this by uncovering the molecular alterations that drive oncogenesis, influence therapeutic response, and determine disease progression. The convergence of these two modalities offers a synergistic diagnostic framework that enhances clinical decision-making across diverse cancer types. Current clinical models demonstrate the efficacy of this integration, such as the WHO’s molecular reclassification of central nervous system tumors and the routine pairing of immunohistochemistry with genomic biomarker profiling in lung and breast cancers. Technological advancements, particularly in artificial intelligence, digital pathology, spatial transcriptomics, and proteogenomics, have further enabled high-resolution, real-time interpretation of tumor biology. These innovations facilitate the transition from conventional diagnostic pathways to comprehensive, multimodal cancer profiling. The Key challenges remain, including the harmonization of multimodal data, standardization of integrative workflows, and equitable access to diagnostic innovations in resource-limited settings. Addressing these barriers is essential for the widespread implementation of integrative oncology practices. The review outlines the clinical significance, technological progress, and translational impact of histogenomic synergy, positioning it as a cornerstone of next-generation personalized oncology. The strategic unification of disciplines across pathology, genomics, and computational science is essential for delivering precise, individualized cancer care on a global scale.
DOI: 10.53555/vh9phy04
Author: Dr. Kalpesh Hathi
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: diamond
OpenAlex ID: W4412474020