Genetic and Molecular Characterization of Ibrutinib-Resistant Mantle Cell Lymphoma: Designing Innovative Therapeutic Strategies

Background

Mantle cell lymphoma (MCL) is a B-cell malignancy with a broad spectrum of clinical, pathological, and biological features, and clinical evolution is usually very aggressive with short responses to treatment and frequent relapses. Ibrutinib is considered the drug of choice in relapsed-refractory cases but patients may develop resistance as some patients in complete remission (CR) have not relapsed yet and are in long term follow-up. The understanding of the resistance mechanisms and the emergence of new drugs targeting key oncogenic mechanisms are providing the basis for designing innovative therapeutic strategies to overcome ibrutinib resistance, both in preclinical studies and preliminary clinical trials.

Methods

We identified differentially expressed genes (DEGs) in 7 ibrutinib-primary resistant MCL patient samples compared with 16 ibrutinib-sensitive MCL patient samples by next generation sequencing (RNA-Seq) and top28-gene signature were developed via Gene Set Enrichment Analysis (GSEA) analysis of RNA-Seq data, and we also verified the expression level of these genes in ibrutinib-resistant and-sensitive MCL patient samples using Real time-PCR, and then a secondary focus of this study was to identify potential predictive biomarkers for therapy in relapsed or refractory MCL. In order to place the gene expression data into a biological context, Ingenuity Pathway Analysis (IPA) software was used to assign the DEGs to know the canonical pathways and functional networks in order to predict the biological functions of the transcriptional changes.

Results

We identified top-28 DEGs in five ibrutinib-resistant MCL patient samples compared with four ibrutinib-sensitive MCL patient samples. We performed gene enrichment and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG pathway) of differentially expressed genes of each samples and verified the predicted genes using Real time-PCR, which were truly related to MCL and not false positive results. Moreover, Using IPA software, we identified that the enriched biological functions in the MCL ibrutinib-resistant patient samples were Oxidative phosphorylation, Mitochondrial Dysfunction and TCA Cycle (Eukaryotic), which were enriched biological functions in the analysis of RNA-Seq data, and which may be targeted by oncogenic events in MCL, and they may influence the tumor response to new therapeutic agents. We also found that expression of these genes (SEPT3, FASN, IDH3A, SLC1A5, INPP5J, CCT5, MTHFD1) was significantly increased in five ibrutinib-resistant MCL patient samples compared with four ibrutinib-sensitive MCL patient samples, and we used IPA to identify some functionally related genes with these genes increased in MCL ibrutinib-resistant patient samples and built networks based on the molecular relationships most relevant to this project.

Conclusion

These data identify a genomic basis for ibrutinib-primary resistance in MCL and provide the important insights into the strategy to address the problem of ibrutinib-resistance, and will hopefully allow more tailored and specific therapies to be designed.