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KRAS/NRAS Mutation-Associated Transcriptional Dysregulation Identifies NRL, CREM and IL-6 as Candidate Prognostic Biomarkers in Multiple Myeloma

Submitted:

21 July 2026

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23 July 2026

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Abstract

Background: Multiple myeloma (MM) is a biologically heterogeneous plasma cell malignancy with variable responses to induction therapy that are not fully explained by current risk stratification systems. Mutations in RAS family genes are prevalent in MM, yet contemporary risk stratification systems do not include them despite their oncogenic potential. Our previous findings showed reduced tumor cell sensitivity to bortezomib-containing triplet induction regimens in the presence of RAS mutations. The aim of this study is to identify RAS pathway–related molecular targets and evaluate their relationship with clinical outcomes. Methods: Forty-four patients with newly diagnosed MM received bortezomib-based induction therapy (VCD or PAD/VCD). Bone marrow CD138+ plasma cells were isolated for transcriptome analysis. KRAS and NRAS gene mutations were identified by Sanger sequencing, and RNA sequencing was performed on the Illumina HiSeq 3000 platform. Gene expression was analyzed using Salmon and DESeq2. The clinical endpoints were depth of response, progression-free survival (PFS), and overall survival (OS). Results: Of 66 candidate RAS-pathway genes examined, five—CREM, NRL, IL-6, MMP14 and MEB2B—showed significantly higher expression in samples with KRAS and NRAS gene mutations (t-test, p < 0.05). Lower NRL gene expression was associated with achieving a deep response (CR/VGPR; p = 0.02). Elevated IL6 gene expression correlated with poorer OS (HR 3.18; p = 0.05), while increased CREM gene expression was associated with shorter PFS (HR 2.62; p = 0.01). Conclusions: Increased expression of NRL, CREM, and IL6 genes could serve as potential prognostic biomarkers in MM and may reflect the molecular mechanisms underlying the adverse effects of KRAS and NRAS gene mutations.

Keywords: 
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1. Introduction

Multiple myeloma (MM) is a biologically heterogeneous plasma cell (PC) neoplasm characterized by a variable clinical course [1,2,3,4,5]. Despite the implementation of modern treatment approaches (bortezomib-based induction therapy, hematopoietic stem cell transplantation, the use of monoclonal antibodies, etc.) and the improvement in risk stratification systems [6,7,8,9], patients with the same disease stage may demonstrate significant differences in MM progression rates and responses to therapy [7,10]. This suggests the insufficient accuracy of existing prognostic models and highlights the need to identify new biomarkers that would allow more reliable assess the depth of treatment response and the risk of an adverse outcome.
Mutations in RAS family genes (NRAS and KRAS) are present in 40–50% of MM patients and increase with disease progression [11,12,13]. The impact of these mutations on survival remains unclear, and published data are contradictory. Some studies have shown that NRAS/KRAS gene mutations are not among the most significant factors affecting MM progression and are considered neutral [13,14]. According to other studies NRAS/KRAS gene mutations unambiguously lead to a worse outcome on bortezomib free therapy regimens [15]. Recent studies have provided evidence of the negative impact of these mutations on the treatment outcome with regimens that include bortezomib [16,17,18].
We previously demonstrated that patients with NRAS/KRAS gene mutations were approximately twice as unlikely to achieve a deep response (complete remission, CR, and very good partial remission, VGPR) to bortezomib-based induction therapy than patients without these mutations [18]. Therefore, investigating the molecular mechanisms that determine the reduced efficacy of induction therapy in the presence of NRAS/KRAS gene mutations is particularly important.
The mechanisms by which NRAS/KRAS gene mutations affect the downstream targets of signaling pathways in MM tumor cells, thereby reducing the effectiveness of induction treatment, remain poorly understood. It has been demonstrated that NRAS/KRAS gene mutations trigger the RAS/ERK signaling cascade, resulting in its constitutive activation [11,19,20,21]. Consequently, phosphorylated ERK activates several transcription factors, resulting in increased expression of cell cycle genes and enhanced PC proliferation [22]. Experimental MM models have demonstrated that mutant NRAS/KRAS proteins simultaneously activate the PI3K/AKT pathway. This results in the suppression of apoptosis, enhanced cell survival and increased cellular metabolic activity [23]. RAS proteins generated as a result of amino acid substitutions associated with mutations in MM tumor cells are capable of activating the NF-κB pathway [22]. Furthermore, it has been demonstrated that NRAS/KRAS mutations enhance proteasome activity by increasing the expression of proteasome subunits and reducing the endoplasmic reticulum stress response [24].
In this study, we investigated the impact of somatic mutations in the NRAS and KRAS genes on the expression levels of genes in tumor cells from patients with MM. We determined the mutation status of the NRAS/KRAS genes and analyzed the transcriptome of bone marrow PC in patients with newly diagnosed MM. Genes expressed significantly differently between patients with and without mutations were selected as candidates for prognostic markers. We then correlated the expression of these genes with the patient’s response to therapy and survival rates.

2. Results

2.1. Identification of Differentially Expressed Genes Associated with Mutations in the NRAS/KRAS Genes in Tumor Cells of Patients with Multiple Myeloma

In order to identify genes whose expression levels change due to NRAS/KRAS gene mutations, we have analyzed downstream targets associated with the RAS/ERK signaling pathways based on the available literature [11,16,19,20,21,22,23,25,26,27,28,29,30,31]. The analysis included 66 genes that regulated by signals transmitted through the RAS cascades (Table 1).
The analysis included 19 patients with NRAS/KRAS gene mutations and 17 patients without mutations; transcriptome analysis was performed for all patients. As a result of the analysis, five genes (CREM, NRL, IL-6, MMP14 and MEF2B) were found to have statistically significant differences in expression between tumor cell samples with NRAS/KRAS gene mutations and control samples (Figure 1, Table 2). Expression was higher in tumor samples with RAS gene family mutations for all five genes. Additionally, in samples with mutations, expression levels of CCND1, MEF2D and MAFA genes were elevated; however, the differences did not reach statistical significance. At the same time, MYC gene transcription levels were lower in cells with NRAS/KRAS gene mutations compared to tumor cells without mutations (Table A1 in Appendix).

2.2. Association of IL-6, CREM, NRL, MMP14, and MEF2B Gene Expression Levels with Therapy Response of MM Patients

In tumor cells of MM patients, expression of IL-6, CREM, NRL, MMP14, and MEF2B genes was elevated in tumor cells with NRAS/KRAS gene mutations. To assess the predictive significance of these genes in MM patients, the expression of the identified genes was analyzed in tumor cells of patients with deep (CR/VGPR, n=19) and non-deep (<VGPR, n=23) response to therapy (Figure 2). Table 3 presents medians and results of Mann–Whitney U test calculations for the expression of CREM, NRL, IL-6, MMP14 and MEF2B genes. The analysis showed that NRL gene expression levels is lower in patients who respond well to therapy (CR+VGPR) compared to those who did not achieve deep response (median 12.1 for deep-responders vs. 28.15 for non-deep-responders, p=0.02).

2.3. The Association of IL-6, CREM, NRL, MMP14 and MEF2B Gene Expression Levels with MM Outcome

The threshold value for each gene used for patient stratification (“low” and “high” expression) was determined based on ROC analysis. According to ROC analysis, the threshold values of expression were 1.2 for IL-6 gene, 2.14 for CREM gene, 1.52 for NRL gene, 2.11 for MMP14 gene, 2.38 for MEF2B gene. OS and PFS were compared between groups of patients with high expression levels of the studied genes (above threshold) and normal expression levels (below or equal to the threshold). Statistical significance of survival estimates and relative risks of adverse outcome from the Cox model are presented in Table 4.
Elevated IL-6 gene expression was an adverse prognostic factor for OS (Figure 3). Kaplan–Meier survival analysis revealed that patients with low IL-6 expression (<1.2) had significantly better survival compared to the high-expression group (≥1.2) (p=0.05). In the Cox proportional hazards regression model, increased IL-6 expression showed a trend toward higher probability of unfavorable outcome (HR=3.18, 95% CI: 0.9–11.3; p=0.07).
Increased CREM gene expression (≥1.2) was associated with reduced PFS (Figure 4). Cox proportional hazards analysis confirmed a statistically significant association of CREM gene expression with worse PFS (HR = 2.62, 95% CI: 1.12–6.09, p = 0.026).

3. Discussion

Our research was focused on investigating how NRAS/KRAS gene mutations influence tumor cell biology and disease progression in MM patients. To this end, we examined the mutational status of NRAS/KRAS genes and expression of 66 RAS/ERK pathway effector genes in tumor cells from MM patients, and tracked the response to induction therapy and the time to progression or death.
Our analysis of target gene expression in the RAS/ERK signaling cascade revealed that NRAS/KRAS gene mutations are associated with specific transcriptomic changes. We identified five out of 66 genes: IL-6, CREM, NRL, MMP14 and MEF2B. The expression of these genes was elevated in samples with NRAS/KRAS gene mutations compared to the samples without mutations. This revealed the most significant targets of the NRAS/KRAS mutations on cellular signaling pathways in tumor PC of the MM patients. The negative impact of the NRAS/KRAS gene mutations on the outcome in patients with MM may be realized through the molecular mechanism proposed in Figure 4.
In our study, elevated NRL gene expression in tumor PC was associated with worse response to induction therapy. These observations were supported by previously published studies: the transcription factor NRL belongs to the MAF protein family [32], which plays an important role in MM pathogenesis [33]. The role of NRL expression in MM had not been previously studied. Our data indicated that high level of IL-6 gene expression might be considered an adverse prognostic factor for MM patients associated with overall survival. This is likely related to the pro-inflammatory effects of this cytokine, activation of signaling pathways, and induction of neoangiogenesis, contributing to tumor progression[27,33,34,35]. IL-6 protein has been previously described as a key growth factor and bone marrow microenvironment cytokine that promotes proliferation, survival, and resistance of tumor cells to MM treatment [27,34,36]. IL-6 is actively produced by microenvironment cells and interacts with receptors on the surface of MM cells, stimulating their growth. At later stages of the disease, tumor PCs independently begin to produce IL-6, autocrinely regulating their growth. Billadeau et al. showed that NRAS/KRAS gene mutations promote the growth of the IL-6-dependent ANBL6 myeloma cell line without the addition of exogenous cytokine [37]. It can be assumed that the appearance of mutations is accompanied by increased IL-6 gene expression in ANBL6 cells. Our study was the first to show that, NRAS/KRAS gene mutations were associated with elevated IL-6 gene expression levels in tumor cells of MM patients. Based on our study and that of Billadeau et al. [37], we concluded that IL-6 secretion, an unfavorable prognostic factor, was activated by NRAS/KRAS gene mutations in MM tumor cells. Association of CREM gene transcription (a transcription factor from the CREB/ATF family) with NRAS/KRAS gene mutations has not been completely understood. It is known that CREM can act as a tumor cell survival factor by creating an immunosuppressive environment in various malignancies [38]. Increased expression of CREB1, a protein from the same CREB/ATF transcription factor family as CREM, contributes to resistance to proteasome inhibitors through the development of tolerance to ER stress [39]. High CREM expression may associate with the activation of cellular stress response mechanisms and increased resistance of tumor cells to apoptosis, leading to reduced PFS. Thus, our data suggest that increased expression of NRL, IL-6 and CREM genes reflect a biologically distinct phenotype of the tumor with NRAS/KRAS gene mutations, which may indicate a previously unknown mechanism of resistance of mutated tumor cells to standard induction therapy in MM patients.

4. Materials and Methods

4.1. Patients

The study included 44 patients with newly diagnosed MM who received first-line chemotherapy at the National Medical Research Center for Hematology, Ministry of Health of the Russian Federation, between January 2013 and November 2019. The patients underwent a comprehensive diagnostic workup, including laboratory and imaging assessments required for disease confirmation and staging according to the International Myeloma Working Group (IMWG) diagnostic criteria (2014). All patients received bortezomib-based triplet induction therapy. Sixteen patients were treated with PAD (bortezomib, doxorubicin, and dexamethasone) and VCD (bortezomib, cyclophosphamide, and dexamethasone), 28 patients received the VCD regimen. Treatment response was evaluated after 4–6 cycles of induction therapy according to the IMWG response criteria (Kumar et al., 2016). Nineteen patients achieved a deep response (CR) or very good partial response (VGPR), whereas 23 patients achieved a partial response (PR) or less (≤PR); response data of two patients were unavailable. The median follow-up ranged from 5 to 84 months.
Baseline patient characteristics are summarized in Table 5.
Transcriptome profiling was performed in all 44 patients; NRAS/KRAS gene mutation analysis was available for 36 patients.

4.2. Isolation of Tumor Cells

CD138+ PCs isolated from bone marrow of MM patients by magnetic separation using CD138 MicroBeads (Miltenyi Biotec GmbH, Germany) on an OctoMACS separator were used for the study. The obtained CD138−/CD138+ fractions were counted, and the purity of isolation was assessed by flow cytometry using anti-CD138-PE antibodies on a BD FACSCanto II (Becton Dickinson, USA). For genomic DNA isolation, cells were lysed in buffer with proteinase K, followed by phenol-chloroform extraction, ethanol precipitation, washing, and dissolution in TE buffer. RNA was isolated by cell lysis in denaturing buffer (Sigma-Aldrich, USA), followed by phenol-chloroform extraction, precipitation, ethanol washing, and dissolution in DEPC-treated water. When PC content in the sample was low, TRIzol with RNA precipitation in the presence of glycogen was used.[references for DNA and RNA isolation]

4.3. Sequencing of NRAS/KRAS Genes

Amplification of exons 2–4 of NRAS and KRAS genes was performed by polymerase chain reaction (PCR) in PCR Master Mix (2X) (Thermo Scientific, USA) in a volume of 25 µL. The reaction mixture contained 0.01–0.02 µg of genomic DNA and 10 pmol of forward and reverse primers (Syntol, Russia). Thermal cycling conditions: 92 °C – 1 min, 60 °C – 1 min, 72 °C – 1 min, 35 cycles. PCR products were purified on columns with quality control by electrophoresis. Sanger sequencing of NRAS/KRAS genes was performed on an ABI PRISM 3500 analyzer (Thermo Fisher Scientific, USA) using forward and reverse primers [40]. Chromatograms were analyzed using Ugene and BioEdit software (reference sequences RefSeq NG_007524 for KRAS and NG_007572 for NRAS).

4.4. RNA Sequencing

RNA sequencing was performed on the Illumina HiSeq 3000 platform (Illumina, USA) using a single-end sequencing kit. Library fragment length was 50 bp. All samples were sequenced in a single run. Sequencing data were deposited in the GEO database under accession number GSE120795. Demultiplexing and conversion to FASTQ format were performed using Illumina Bcl2fastq2 v.2.17. Quality control was performed using FastQC v.0.11.8 and MultiQC v.1.26.
Gene expression analysis was performed using Salmon [41] in quasi-mapping mode using the GENCODE v32 reference transcriptome; aggregation from transcript level to gene level was performed using tximport [42,43], and Ensembl identifiers were converted to HGNC gene symbols using biomaRt [44]. Data normalization and gene expression calculation were performed using DESeq2 (v.1.26.0) in R environment [45].

4.5. Statistical Analysis

For categorical variables, Fisher’s exact test and χ2 test were used, and odds ratios (OR) with 95% CI were calculated. Comparison of quantitative variables was performed using Student’s t-test or Wilcoxon test. Data are presented as mean ± standard deviation or median with IQR.
The threshold value for each gene, which was used to stratify patients as having “low” or “high” expression, was assessed by ROC analysis, with the threshold being determined by the Youden index. The determined thresholds of gene expression were then compared with the gene expression range in donor samples (Appendix, Table A2). We found that the determined thresholds corresponded to the upper boundaries of the expression ranges in the donor samples. PFS and OS analysis was performed using the Kaplan–Meier method, differences were assessed by log-rank test, and factor influence was assessed by Cox model with HR and 95% CI calculation. Differences were considered statistically significant at p < 0.05.

5. Conclusions

Hyperexpression of CREM, NRL, IL-6, MMP14, and MEF2B genes was detected in tumor cells with NRAS/KRAS mutations, suggesting these genes as potential targets involved in mechanisms mediating the negative effect of RAS family mutations. Expression of NRL, CREM, and IL-6 genes is associated with reduced therapy efficacy, PFS, and OS, respectively. The identified associations between expression and adverse disease outcomes emphasize the important role of the RAS/ERK cascade in MM progression.

Author Contributions

Conceptualization, A.Se. and Y.S.; methodology, A.Se., Y.C., S.K.; resources, M.S. and. L.M.; validation, A.Se.; formal analysis, A.Se. and Y.C.; investigation, A.Sе.; data curation, A.Sе.; writing—original draft preparation, A.Se.; writing—review and editing, Y.S. and A.Su.; visualization, Y.C.; supervision, Y.S.; project administration, Y.S. and A.Su. All authors have read and agreed to the published version of the manuscript.”.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of National Medical Research Center for Hematology (protocol code 174 and 28.09.2023).

Data Availability Statement

Data available from authors upon reasonable request.

Acknowledgments

The authors are grateful to Dr. Grachev for providing bone marrow samples from a subset of the patients; to Dr. Bigildeev and Dr. Schneyderman for their valuable advice on the experimental design of the molecular biology part of this work. The authors also thank Natalia Sergeeva, Natalia Pylaeva, and Rostislav Borodin for their useful advice and assistance in creating the illustration with the aid of ChatGPT. Figure 4 was created with the assistance of ChatGPT (OpenAI). The authors reviewed and edited the generated content and take full responsibility for the final figure.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
MM Multiple myeloma
BM Bone marrow
PCs Plasma cells
RAS Rat sarcoma proto-oncogene family
KRAS Kirsten rat sarcoma viral oncogene homolog
NRAS Neuroblastoma RAS viral oncogene homolog
ERK Extracellular signal-regulated kinase
PI3K Phosphoinositide 3-kinase
AKT Protein kinase B
NF-κB Nuclear factor kappa B
IL-6 Interleukin-6
VCD Bortezomib, cyclophosphamide, dexamethasone
PAD Bortezomib, doxorubicin, dexamethasone
PFS Progression-free survival
OS Overall survival
CR Complete response
VGPR Very good partial response
PR Partial response
IMWG International Myeloma Working Group
ISS International Staging System
R-ISS Revised International Staging System
ROC Receiver operating characteristic
HR Hazard ratio
CI Confidence interval
IQR Interquartile range
PCR Polymerase chain reaction
RNA Ribonucleic acid
DNA Deoxyribonucleic acid
GEO Gene Expression Omnibus
FASTQ FASTQ sequence format
VST Variance-stabilizing transformation
HGNC HUGO Gene Nomenclature Committee
DEPC Diethyl pyrocarbonate

Appendix A

Table A1. Effector target genes of the RAS/ERK signaling cascade. Results of the statistical analysis comparing two groups are presented: patients with NRAS/KRAS gene mutations and patients without mutations. Gene expression levels, measured as VST- normalized gene counts, presented on a logarithmic scale. Genes highlighted in red show statistically significant differences in expression levels in the group of patients with NRAS/KRAS gene mutations compared with the group without these mutations.
Table A1. Effector target genes of the RAS/ERK signaling cascade. Results of the statistical analysis comparing two groups are presented: patients with NRAS/KRAS gene mutations and patients without mutations. Gene expression levels, measured as VST- normalized gene counts, presented on a logarithmic scale. Genes highlighted in red show statistically significant differences in expression levels in the group of patients with NRAS/KRAS gene mutations compared with the group without these mutations.
Gene Patients without NRAS/KRAS mutations, mean Patients with NRAS/KRAS mutations, mean Significance level,
p value
Patients without NRAS/KRAS mutations, SD Patients with NRAS/KRAS mutations, SD
с-JUN 9.08 9.24 0.65 1.07 1.00
JUNB 8.29 8.12 0.68 1.24 1.17
JUND 8.29 8.52 0.39 0.83 0.73
c-FOS 8.90 9.27 0.16 0.82 0.74
FOSB 9.69 9.85 0.53 0.83 0.70
Fra-1 2.61 2.69 0.86 1.19 1.28
Fra-2 5.96 5.61 0.35 1.34 0.88
CREB 6.17 6.02 0.38 0.27 0.66
CREM 4.52 4.78 0.03 0.39 0.29
ATF-1 4.80 4.76 0.85 0.55 0.46
CREB-2 (ATF-4) 8.47 8.37 0.50 0.38 0.49
CREB-3 6.04 6.13 0.47 0.38 0.34
CREB-5 3.65 4.35 0.25 1.98 1.55
ATF-2 (CRE-BP1) 6.10 6.23 0.14 0.27 0.26
ATF-3 5.89 6.09 0.61 1.21 1.09
ATF-5 (ATFX) 6.22 6.23 0.99 1.39 1.31
ATF-6 7.10 7.03 0.69 0.57 0.41
ATF-7 5.72 6.04 0.09 0.56 0.53
B-ATF 1.26 1.24 0.97 1.82 1.77
MAF 4.46 4.18 0.71 2.30 2.22
MAFA 0.71 1.39 0.10 0.82 1.45
MAFB 3.99 3.78 0.75 2.24 1.52
NRL 2.38 3.13 0.03 1.19 0.78
CCND1 5.39 7.44 0.06 3.25 3.13
VEGF 6.69 6.50 0.33 0.54 0.56
EGFR 0.32 0.43 0.73 0.84 1.03
FGFR1 4.38 4.34 0.84 0.73 0.61
BCL2 7.85 7.69 0.34 0.55 0.46
BCL2L1 6.73 6.63 0.59 0.39 0.65
BCL2L2 5.40 5.52 0.48 0.42 0.60
MCL1 9.73 9.49 0.15 0.43 0.55
BAX 5.39 5.60 0.20 0.52 0.44
BCL2A1 3.56 3.08 0.40 1.67 1.68
BAK1 5.71 5.68 0.82 0.50 0.47
BOK 0.15 0.53 0.19 0.64 1.01
BCL2L10 0.77 0.69 0.80 0.95 0.87
BCL2L12 4.34 4.68 0.30 1.29 0.55
BCL2L13 5.86 5.82 0.71 0.28 0.38
BCL2L14 3.88 3.58 0.23 0.67 0.78
BCL2L15 4.97 5.05 0.79 0.71 0.95
BNIP2 6.53 6.35 0.18 0.36 0.42
BCLXL 6.73 6.63 0.59 0.39 0.65
BIRC5 4.52 4.61 0.62 0.46 0.51
IL-6 0.93 2.40 0.02 1.42 2.17
IL6R 7.46 7.11 0.35 1.10 1.14
TNF-alpha 2.32 2.37 0.95 2.33 2.26
MMP2 0.85 1.26 0.34 1.26 1.28
MMP8 4.03 3.73 0.64 1.29 2.30
MMP9 4.29 4.55 0.69 1.66 2.06
MMP11 4.06 3.98 0.71 0.40 0.78
MMP13 0.80 0.91 0.70 0.63 0.95
MMP14 2.39 3.29 0.04 1.54 0.92
MMP15 1.20 1.18 0.97 1.63 1.54
MMP16 2.46 2.22 0.76 2.42 2.28
MMP17 0.96 1.34 0.48 1.30 1.85
MMP19 2.56 2.34 0.70 1.76 1.64
MMP21 1.66 2.03 0.27 0.99 0.98
MMP23B 1.71 2.22 0.22 0.92 1.40
MMP25 2.99 3.21 0.73 1.79 1.91
C-MYC 7.16 6.37 0.06 1.29 1.18
p21 7.31 7.55 0.38 0.73 0.86
p27 6.80 6.93 0.46 0.46 0.55
MEF2A 6.75 6.66 0.37 0.31 0.25
MEF2B 4.99 6.08 0.00 0.96 1.03
MEF2C 8.02 7.92 0.65 0.73 0.47
MEF2D 7.65 7.86 0.08 0.33 0.38
Table A2. Expression level ofIL-6, CREM, NRL, MMP14, and MEF2B genes in donor samples. Gene expression levels presented on a logarithmic scale.
Table A2. Expression level ofIL-6, CREM, NRL, MMP14, and MEF2B genes in donor samples. Gene expression levels presented on a logarithmic scale.
Samples Gene expression level, VST- normalized gene counts
CREM NRL IL-6 MMP14 MEF2B
D1 1.91 1.00 1.13 1.46 1.75
D11 1.73 0.40 0.91 1.79 1.93
D2 1.93 1.05 1.16 0.54 1.84
D3 2.09 1.52 1.11 1.94 2.38
D5 2.14 1.32 0.63 2.11 2.19
D7 1.83 1.39 1.22 1.90 2.33
D9 1.99 1.17 0.85 1.74 2.09
Gene expression level (max) 2.14 1.52 1.22 2.11 2.38

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Figure 1. Expression levels of protein kinase cascade target genes in tumor cells with and without NRAS/KRAS gene mutations. Only genes with statistically significant differences (p < 0.05) are shown: CREM, IL-6, NRL, MMP14 and MEF2B. Each point represents expression value in one sample; horizontal lines represent median and IQR. RAS – patients with NRAS/KRAS gene mutations, wt - patients without mutations.
Figure 1. Expression levels of protein kinase cascade target genes in tumor cells with and without NRAS/KRAS gene mutations. Only genes with statistically significant differences (p < 0.05) are shown: CREM, IL-6, NRL, MMP14 and MEF2B. Each point represents expression value in one sample; horizontal lines represent median and IQR. RAS – patients with NRAS/KRAS gene mutations, wt - patients without mutations.
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Figure 2. Expression levels of protein kinase cascade target genes in patients with deep response to therapy (CR+VGPR) and non-deep response (<VGPR). Each symbol represents one sample and one patient. Horizontal lines represent median and IQR.
Figure 2. Expression levels of protein kinase cascade target genes in patients with deep response to therapy (CR+VGPR) and non-deep response (<VGPR). Each symbol represents one sample and one patient. Horizontal lines represent median and IQR.
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Figure 3. a) OS in MM patients depending on IL-6 gene expression level. Vertical axis – proportion of surviving patients. Red line – patients with elevated IL-6 gene expression. Blue line – patients with normal IL-6 expression; b) PFS in MM patients depending on CREM gene expression level. Vertical axis – proportion of patients without relapse/progression. Red line – patients with elevated CREM gene expression. Blue line – patients with normal CREM gene expression.
Figure 3. a) OS in MM patients depending on IL-6 gene expression level. Vertical axis – proportion of surviving patients. Red line – patients with elevated IL-6 gene expression. Blue line – patients with normal IL-6 expression; b) PFS in MM patients depending on CREM gene expression level. Vertical axis – proportion of patients without relapse/progression. Red line – patients with elevated CREM gene expression. Blue line – patients with normal CREM gene expression.
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Figure 4. Proposed mechanism of negative impact of NRAS/KRAS gene mutations through downstream biochemical cascades in tumor cells of the patients with MM.
Figure 4. Proposed mechanism of negative impact of NRAS/KRAS gene mutations through downstream biochemical cascades in tumor cells of the patients with MM.
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Table 1. Target genes of RAS cascades and their functional groups.
Table 1. Target genes of RAS cascades and their functional groups.
Genes expression evaluated Functional Group
c-JUN, JUNB, JUND, c-FOS, FOSB, Fra-1, Fra-2, CREB, CREM, ATF-1, CREB-1, CREB-2 (ATF-4), CREB-3, CREB-5, ATF-2 (CRE-BP1), ATF-3, ATF-5 (ATFX), ATF-6, ATF-7, B-ATF, MAF, MAFA, MAFB, NRL Early response to mitogenic stimuli
CCND1, p21, p27, c-MYC, VEGF, EGFR, FGFR1 Cell proliferation
BCL2, BCL2L1, BCL2L2, MCL1, BAX, BCL2A1, BAK1, BOK, BCL2L10, BCL2L12, BCL2L13, BCL2L14, BCL2L15, BNIP2, BCLXL, BIRC5 Apoptosis
IL-6, IL6R, TNF-alpha Inflammation
MMP2, MMP8, MMP9, MMP11, MMP13, MMP14, MMP15, MMP16, MMP17, MMP19, MMP21, MMP23B, MMP25 Metastasis
MEF2A, MEF2B, MEF2C, MEF2D Differentiation and survival
Table 2. Gene expression levels in patients with and without NRAS/KRAS gene mutations.
Table 2. Gene expression levels in patients with and without NRAS/KRAS gene mutations.
Gene Patients without NRAS/KRAS mutations Patients with NRAS/KRAS mutations Significance level,
p value
Median [IQR], VST-normalized counts
CREM 89.0 [68.7-113.4] 117.4 [104.7-154.7] 0.03
NRL 11.1 [8.4-19.4] 28.2 [13.0-44.4] 0.03
IL6 1.4 [0-3.5] 6.6 [1.0-88.4] 0.024
MEF2B 144.4 [67.9-307.6] 620.5 [152.7-955.3] 0.04
MMP14 14.7 [3.5-34.5] 21.8 [16-51.9] 0.002
Table 3. Assessment of transcriptional activity of protein kinase cascade target genes in patients with deep (CR+VGPR) and non-deep (<VGPR) response to induction therapy.
Table 3. Assessment of transcriptional activity of protein kinase cascade target genes in patients with deep (CR+VGPR) and non-deep (<VGPR) response to induction therapy.
Gene Patients achieving CR+VGPR Patients achieving <VGPR Significance level, p value
Median [IQR], VST-normalized counts
CREM 110.2 [89.3-156.7] 104.8 [72.7-159.3] 0.20
NRL 12.1 [4.2-20.2] 28.1 [12.0-45.4] 0.02
IL6 1.6 [1.0-81.4] 2.6 [1.0-31.7] 1.00
MEF2B 232.3 [74.0-620.5] 356.7 [120.8-144.0] 0.58
MMP14 16.6 [7.6-31.5] 27.5 [10.8-54.3] 0.24
Table 4. Correlation of OS and PFS with IL-6, CREM, NRL, MMP14 and MEF2B gene expression levels.
Table 4. Correlation of OS and PFS with IL-6, CREM, NRL, MMP14 and MEF2B gene expression levels.
Overall Survival
Gene Long rank test, p value Cox model
Hazard
Ratio
95% CI
(lower)
95% CI
(upper)
Significance level, p value
CREM 0.15 2.44 0.70 8.44 0.16
NRL 0.54 0.62 0.13 2.93 0.55
IL6 0.05 3.18 0.90 11.30 0.07
MMP14 0.50 2.02 0.25 16.24 0.51
MEF2B 0.31 0.50 0.13 1.94 0.32
Progression Free Survival
Gene Long rank test, p value Cox model
Hazard
Ratio
95% CI
(lower)
95% CI
(upper)
Significance level, p value
CREM 0.01 2.62 1.12 6.09 0.03
NRL 0.58 1.29 0.53 3.15 0.58
IL6 0.25 1.61 0.71 3.69 0.26
MMP14 0.75 1.40 0.19 10.46 0.75
MEF2B 0.93 1.04 0.46 2.35 0.93
Table 5. Patient characteristics at diagnosis.
Table 5. Patient characteristics at diagnosis.
Parameter Total number of patients, n (%)
Sex (male/female) 27 (61.4) / 17 (38.6)
Median age, years (range) 59 (28-78)
Durie-Salmon stage (I/ II/ III/unknown) 3 (6.8) / 15 (34.1) / 25 (56.8) / 1 (2.3)
ISS stage (I/ II/ III/ unknown) 4 (9.1) / 5 (11.4) / 31 (70.4) / 4 (9.1)
R-ISS stage (I/ II/ III/ unknown) 1 (2.3) /3 (6.8) /30 (68.2) /10 (22.7)
Cytogenetics (done/ unknown)
  • t(4;14) (positive/negative)
  • t(14;16) (positive/negative)
  • del17p (positive/negative)
30 (68.2)/14 (31.8)
3 (10) / 27 (90)
3 (10) / 27 (90)
4 (13.3) / 26 (86.7)
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