An Integrated Next Generation Sequence Analysis of Blood Cancer Along with Biopython

Blood cancers, including leukaemia, lymphoma, and myeloma, are among the most prevalent haematological malignancies. PDE6D, a key regulator of oncogenic RAS signalling, has been implicated in cancer progression. This study integrates Next-Generation Sequencing (NGS) with computational bioinformatics to analyse PDE6D mutations and their role in blood cancer pathogenesis. The 7PAC protein structure (PDE6D) was retrieved from the Protein Data Bank and analysed using PyMOL for structural visualization. Sequence alignment and homology studies were conducted using BLAST and Cluster Omega. Root Mean Square Deviation (RMSD) analysis assessed structural variations, while protein enrichment analysis and pathway analysis explored PDE6D’s role in oncogenic signalling. B-factor analysis identified dynamic regions susceptible to mutation. BioPython was employed for genomic data analysis and functional annotation. STRING analysis revealed significant PDE6D interactions, particularly with RPGR, suggesting its involvement in cellular processes. KEGG pathway analysis confirmed its role in RAS-driven leukaemia. Root mean square analysis indicated high structural conservation, while B-factor analysis highlighted mutation-prone regions. Bioinformatics analysis suggested PDE6D mutations may contribute to dysregulated RAS signalling in blood cancers. This study highlights PDE6D as a potential biomarker and therapeutic target in blood cancer. By integrating NGS with bioinformatics tools, we identified critical genetic variations affecting its oncogenic role. Further in vitro and in vivo studies are required to validate PDE6D-targeted therapies, advancing precision medicine for blood cancer treatment.