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ARTICLE

Concordant Shared Transcriptomic Signatures and Candidate Regulatory Features in Chronic Lymphocytic Leukemia and Multiple Myeloma

Abtin Tondar1,2,*, David Hervás Marín3, Laura Calvet Liñán4, Asim Kumar Bepari5
1 Interuniversity Doctoral Program in Bioinformatics, Department of Computer Science, Multimedia and Telecommunication, Universitat Oberta de Catalunya (UOC), Barcelona, Spain
2 Stanford Deep Data Research Computing Center, Stanford University, Stanford, CA, USA
3 Department of Applied Statistics and Operations Research and Quality, Universitat Politècnica de València (UPV), Valencia, Spain
4 Telecommunications and Systems Engineering Department, Universitat Autònoma de Barcelona (UAB), Sabadell, Spain
5 Department of Pharmaceutical Sciences, North South University (NSU), Dhaka, Bangladesh
* Corresponding Author: Abtin Tondar. Email: email
(This article belongs to the Special Issue: Machine Learning for Precision Oncology: From Bench to Bedside)

Oncology Research https://doi.org/10.32604/or.2026.082424

Received 16 March 2026; Accepted 24 June 2026; Published online 23 July 2026

Abstract

Background: Chronic lymphocytic leukemia (CLL) and multiple myeloma (MM) are B-cell malignancies with distinct cellular origins and microenvironmental dependencies. We aimed to identify concordant transcriptomic signatures and candidate transcriptional regulatory features between CLL CD19-positive B cells and MM-associated bone marrow-derived mesenchymal stromal cells (MSCs). Methods: Public Gene Expression Omnibus bulk RNA sequencing datasets were analyzed separately within each context using DESeq2. Differentially expressed genes (DEGs) were defined using adjusted p-value < 0.05 and absolute log2 fold change > 1. Cross-disease analyses assessed overlap, directionality, log2 fold-change concordance, expressed-gene background-adjusted enrichment, coexpression structure, and transcription factor annotation. Results: We found a focused concordant gene-level signature shared across contexts. We identified 5965 DEGs in CLL and 1021 DEGs in MM; 323 were shared, and 262 were concordantly regulated, including 52 upregulated and 210 downregulated genes in both contexts. These genes showed strong log2 fold change concordance between CLL and MM. No Gene Ontology or Kyoto Encyclopedia of Genes and Genomes terms remained significant after expressed-gene background correction, supporting stronger gene-level than pathway-level evidence. Exploratory coexpression analysis identified PSMA3-AS1, SNORD58A, 100124516, MSS51, and 652966 as the top degree-ranked hubs and seven shared differentially expressed transcription factor candidates: MAFB, MYB, CCDC17, MYSM1, ZMAT1, ZNF491, and ZNF789. Expression-matched permutation analysis did not support global transcription factor enrichment. Conclusion: These findings support a cross-contextual concordant transcriptomic signature shared by CLL CD19-positive B cells and MM-associated MSCs, warranting validation in harmonized cohorts and experiments.

Keywords

Chronic lymphocytic leukemia; multiple myeloma; differential gene expression; transcriptomics; coexpression network; transcriptional regulation

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