J Hematol Mult Myeloma | Volume 6, Issue 1 | Review Article | Open Access

Multiomics Analysis on the Clinical Treatment for Multiple Myeloma (MM)

Ruby Srivastava

Bioinformatics, Centre for Cellular and Molecular Biology-CSIR, India

^*Correspondance to: Ruby Srivastava 

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Abstract

The innovative speed in Multiple Myeloma (MM) therapy is remarkable in recent years with the arrival of monoclonal antibodies and approval of novel agents with new action mechanisms. Emerging therapies especially immunotherapy Chimeric Antigen Receptor (CAR)-T cells, Bispecific T-cell Engager Antibodies (BiTEs), Antibody-Drug Conjugates (ADCs), newer generations of Monoclonal Antibodies (MoAbs) and small molecule inhibitors/modulators have extended the survival of a patient, advancing with the goal of a cure. In this work, AI driven tools are used for multinomics (GSE156872) studies on the homosapiens and mus musculus. The transcriptomics data showed 37 downregulated genes (homosapiens) and 9 downregulated genes (mus musculus), which indicated them to be the potential targets for pathogenesis, diagnosis and treatment. Transcription Factor (TF) -gene interactions were seen for ID3, C3, CFBPD, ZNF267, hsr-mir-98- 5p and RDGBRA human tumor genes whereas Esr1, Id4, Foxa1, mmu-mir-425-5p and mmu-mir186-5p TF gene interactions were observed for mus musculus. The ChIP-seq analysis showed a lower peak of NSD2 in humans and higher in mus musculus. The different level of epigenetics in both (human, mice) indicated that the target might not be used for further analysis in mice for knockin and knock-out or further pharmacokinetics analysis. Integrated KEGG Pathways analysis from (DEGs-ChIP) data predicts carcinogenesis for humans and mus musculus. Drug-gene interaction predicted few approved drugs and immunotherapies for the personalized treatment of MM patients. Bioinformatics studies suggested a combination therapy, which is seen in clinical treatment as well.

Keywords:

Multiple myeloma; Bone marrow; Transcriptomics; Epigenomics; Malignancy

Citation:

Srivastava R. Multiomics Analysis on the Clinical Treatment for Multiple Myeloma (MM). J Hematol Mult Myeloma. 2023; 6(1): 1028..