Candidate miRNA Regulators of Blood Transcriptional Signatures for Differential Diagnosis of Chronic Lymphocytic Leukemia and Multiple Myeloma: A Comprehensive In Silico Study

Chronic lymphocytic leukemia (CLL) and multiple myeloma (MM) are biologically distinct hematologic malignancies with heterogeneous clinical courses, and minimally invasive molecular biomarkers are needed to support blood-based discrimination. We performed a comprehensive in silico analysis to derive cross-cohort, direction-consistent transcriptomic programs for CLL and MM and to nominate regulatory microRNAs (miRNAs) linked to these signatures. Public gene-expression datasets from the NCBI Gene Expression Omnibus (two cohorts per disease) were processed with a reproducible workflow to define disease-biased consensus gene sets. Experimentally validated miRNA–target interactions from miRTarBase were integrated with consensus genes for miRNA target over-representation analysis, and miRNA–mRNA networks were constructed to prioritize candidate miRNAs by connectivity. A strict intersection strategy yielded a large, direction-consistent CLL consensus program, whereas a vote-based approach produced a smaller MM program due to a weaker signal in one cohort. Enrichment and network analyses identified compact regulatory modules in CLL, including a highly connected candidate miRNA linked to many CLL-up genes. This framework provides reproducible disease-biased gene programs and evidence-anchored miRNA candidates to support targeted experimental validation and the development of hypothesis-driven blood-based biomarker studies for differential diagnosis and monitoring.