Page 271 - Haematologica March 2020

Kinome profiling to target Multiple Myeloma
become resistant to any treatment, resulting in loss of clin- ical control over the disease. It thus remains an unmet need for new therapeutic approaches to improve treat- ment of MM patients.
Protein kinases are key actors in various cancers where they are involved in proliferation, survival, migration but also drug resistance.6 Protein kinases have been a potent source of targets for cancer treatment with inhibitors already approved or in clinical evaluation in numbers of malignancies. Kinases represent interesting druggable tar- gets in MM. Indeed, whereas major signaling pathways have been studied in myeloma, they only represent a small proportion of the whole kinome.7
In a first study, Tiedemann and colleagues8 used a high- throughput systematic RNA interference approach to investigate kinome expression in human myeloma cell lines (HMCL) and identified potential new targets for MM therapy. Here, we investigated the kinome expression pro- filing in large cohorts of MM patients to identify key tar- gets and new synergistic combinations with conventional treatment. We used a list of kinases or kinase-related genes9 and investigated the prognostic impact of the kinome expression profile in MM. We identified 36 kinas- es significantly involved in patient’s outcome in three independent cohorts and further analyzed the potential impact of selected available kinases inhibitors in HMCL and primary human myeloma cells. We thus provide a list of protein kinases representing potent therapeutic targets for high-risk MM patients and propose new synergistic combinations of kinase inhibitors and conventional MM treatment.
Methods
Gene expression profiling and statistical analyses
We used the gene expression profiling (GEP) from three inde- pendent cohorts constituted of MM cells (MMC) purified from untreated patients: the Heidelberg-Montpellier cohort of 206 patients (ArrayExpress public database under accession number E-MTAB-362)10,11 the UAMS-TT2 cohort of 345 patients from the University of Arkansas for Medical Sciences (UAMS, Little Rock, AR, USA; accession number GSE2658),12 and the UAMS-TT3 cohort of 158 patients (E-TABM-11,38 accession number GSE4583).13 Gene expression data were normalized with the MAS5 algorithm and processing of the data was performed using the webtool genomicscape (http://www.genomicscape.com).14 STRING webtool (https://string-db.org) was used to evaluate inter- connections between genes and analyzed the enriched pathways. Cluster (v2.11) and Tree View were used to visualize gene expres- sion data.15 Univariate and multivariate analysis of genes prognos- tic for patients’ survival was performed using the Cox proportion- al hazard model.
Multiple myeloma cell lines
HMCL AMO-1 and OPM2 were purchased from DSMZ (Braunschweig, Germany), XG1 and XG21 were obtained as described.16 HMCL were cultured in RPMI 1640 medium, 10% foetal calf serum (FCS) (control medium). For XG - IL-6 dependent HMCL, 2ng/mL IL-6 was added. Cells were cultured in 96-well flat-bottom microtiter plates in the presence of a concentration range of selected compounds: AZD7762/CHK1i and OTSSP167/MELKi (Selleck, euromedex), HITOPK032/PBKi, XL413/CDC7-DBF4i, SRPIN340/SRPK1i (Sigma), AZ3146/MPS1i, Centrinone B/PLK4i (Tocris). Cell Titer Glo Luminescent Assay
(Promega, Madison, WI, USA) was used to assess cell viability, and the 50% inhibition (IC50) was determined using GraphPad Prism software (http://www.graphpad.com/scientific-software/prism/).
The 5T33vv cells originated spontaneously in aging C57BL/KaLwRij mice and have since been propagated in vivo by intravenous transfer of the diseased marrow in young syngeneic mice.17
Primary multiple myeloma cells
Bone marrow of patients presenting with previously untreated MM (n=5) at the University Hospital of Montpellier was obtained after patients' written informed consent in accordance with the Declaration of Helsinki and agreement of the Institutional Review Board and the Montpellier University Hospital Centre for Biological Resources (DC-2008-417). Primary myeloma cells of patients were cultured with or without graded concentrations of selected inhibitors and MMC cytotoxicity was evaluated using anti-CD138-Phycoerythrin monoclonal antibody (clone B-A38) and CD38-Allophycocyanin (clone-LS198-4-3) (Beckman-Coulter) as described.11 In each culture group, viability (trypan blue) and cell counts were assayed and the percentage of CD138+ viable myeloma cells was determined by flow cytometry.
Additional information concerning the methodology are includ- ed in the Online Supplementary Materials and Methods.
Results
Identification of 36 kinome-related targets linked to prognosis in three independent MM cohorts
Considering the crucial role played by protein kinases in pathologies, including MM, we first aimed to identify kinome-related genes associated with prognostic value in MM. A list of 661 genes extracted from the literature, rep- resenting 661 kinases or kinase-related genes9 (Online Supplementary Table S1) were thus tested for their prognos- tic value in the Heidelberg-Montpellier cohort (n=206) using the Maxstat algorithm.10,11 Among the 661 genes investigated, the expression of 104 demonstrated a signif- icant prognostic value after Benjamini Hochberg multiple testing correction. We searched to validate the prognostic value of the 104 selected kinases in two other independent cohorts of newly diagnosed patients (UAMS-TT212 and UAMS-TT313) and defined a final list of 36 kinases with significant prognostic value in the three cohorts (Figure 1A and Online Supplementary Table S2). Among the 36 kinase or kinase-related genes identified, eight of them were associated with a favorable prognosis (AZU1; CDKN1A; DDR1; HK3; MAP4K2; MERTK; PRKCSH; TESK2), while 28 demonstrated a poor prognostic value (AURKA; BUB1; BUB1B; CDC7; CDKN2C; CDKN3; CHEK1; CKS1B; CKS2; DBF4; DUSP10; HK2; PI4K2B; MAP2K6; MELK; NEK2; NTRK3; PAK2; PBK; PFKP; PLK4; PTPRG; RPRD1A; SRPK1; SRPK2; STK39; TK1; TTK).
Analysis of their involvement in cellular physiology highlighted the cell cycle as the top Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway (Figure 1B), and string network of the 36 genes showed highly intercon- nected proteins particularly for those with a role in cell cycle (Figure 1C).
Hierarchical clustering underlined a spread expression of the genes among MM patients, except for a cluster composed of 14 kinases related to proliferation/mitosis (CDKN2C; CDC7; CDKN3; BUB1B; MELK; BUB1; AURKA; NEK2; PBK; TTK; CHEK1; PLK4; CKS1B and
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