RNA-Seq and XAI Can be Used as Tools to Aid Pathologists in the Process of Cancer Diagnosis

RNA sequencing (RNA-Seq) is an advanced technique that enables the comprehensive analysis of gene expression and the transcriptome in biological samples with exceptional precision and scalability. Leveraging platforms like Illumina, PacBio, and Oxford Nanopore, RNA-Seq has revolutionized cancer research by identifying genes, isoforms, and genetic variants. When combined with bioinformatics tools, it allows the detection of gene expression signatures, alternative splicing events, and profiles of non-coding RNAs. Furthermore, single-cell analysis provides insights into tumor heterogeneity, enhancing diagnostics, prognostics, and the development of personalized therapies.Artificial intelligence (AI), particularly explainable AI (XAI), plays a pivotal role in transcriptomic data analysis. Interpretable models, such as regression analyses or decision trees, and post-hoc techniques like LIME and SHAP, improve the reliability and usability of findings by identifying key genes for clinical decision-making. These tools integrate seamlessly with high-resolution single-cell and three-dimensional analyses, exploring intratumoral heterogeneity and cellular signaling pathways.Addressing the heterogeneity of common cancers demands the integration of sequencing technologies and AI. The combination of short- and long-read RNA-Seq enables the identification of isoforms and splicing events critical to cancer biology. Together, these technologies and approaches optimize diagnostic and therapeutic strategies, paving the way for personalized treatments by detecting and characterizing genetic alterations and their impact on the tumor microenvironment.