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Article

MicroRNA: A Signature for the Clinical Progression of Chronic Lymphocytic Leukemia

by
Yuliya A. Veryaskina
1,2,*,
Sergei E. Titov
1,3,
Igor B. Kovynev
4,
Tatiana I. Pospelova
4,
Sofya S. Fyodorova
4,
Yana Yu. Shebunyaeva
4,
Sergei A. Demakov
1,
Pavel S. Demenkov
5 and
Igor F. Zhimulev
1
1
Laboratory of Molecular Genetics, Department of the Structure and Function of Chromosomes, Institute of Molecular and Cellular Biology, SB RAS, 630090 Novosibirsk, Russia
2
Laboratory of Gene Engineering, Institute of Cytology and Genetics, SB RAS, 630090 Novosibirsk, Russia
3
AO Vector-Best, 630117 Novosibirsk, Russia
4
Department of Therapy, Hematology and Transfusiology, Novosibirsk State Medical University, 630091 Novosibirsk, Russia
5
Laboratory of Computer Proteomics, Institute of Cytology and Genetics, SB RAS, 630090 Novosibirsk, Russia
*
Author to whom correspondence should be addressed.
Lymphatics 2024, 2(3), 157-167; https://doi.org/10.3390/lymphatics2030013
Submission received: 21 May 2024 / Revised: 30 June 2024 / Accepted: 1 August 2024 / Published: 13 August 2024
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Abstract

:
Chronic lymphocytic leukemia (CLL) is the most common human leukemia. The disease is caused by abnormal proliferation and development of lymphocytes and their precursors in the blood and bone marrow (BM). Recent studies have shown that the CLL’s clinical course and outcome depend not only on genetic but also epigenetic factors. MicroRNAs (miRNAs) are involved in the development of hematological tumors, including CLL. The aim of this study is to identify the miRNA expression profile in CLL and determine the role of miRNAs in biological pathways associated with leukemogenesis in CLL. The following samples were used in this study: (1) samples obtained by sternal puncture and aspiration biopsy of BM (n = 115). They included samples from 21 CLL patients with anemia and indications for therapy and 45 CLL patients without anemia and with indications for therapy. The control group for the CLL BM samples consisted of patients with non-cancerous blood diseases (n = 35). (2) Lymph node (LN) samples (n = 20) were collected from CLL patients. The control group for the CLL LN samples consisted of patients with lymphadenopathy (n = 37). All cases were patients before treatment. We demonstrated a significant upregulation of miRNA-34a and miRNA-150 in CLL BM samples (p < 0.05) and downregulation of miRNA-451a in CLL LN samples (p < 0.05). We noted a dynamic increase in the levels of miRNA-150 and miRNA-34a in BM at various stages of tumor progression of CLL. We concluded that a dynamic picture of clinical manifestations of CLL closely correlates with changes in epigenetic characteristics of the tumor. Progression of the lymphoproliferative process and indications for cytoreductive therapy are associated with changes in the miRNA profile generated by cancer cells in different sites of clonal expansion.

1. Introduction

Chronic lymphocytic leukemia (CLL) is the most common human leukemia [1]. This disease is characterized by clonal expansion of CD5+ and CD23+ B cells in the blood, bone marrow (BM), and secondary lymphoid tissues [2]. The clinical picture of CLL is heterogeneous: it ranges from an indolent, slowly progressive course with almost normal life expectancy in patients to rapidly progressive disease forms with low survival rates. Some CLL cases transform into a very aggressive form of hemoblastosis, known as Richter’s syndrome [3].
Chromosomal aberrations are found in more than 80% of cases of tumor lymphocytes, which makes it possible to differentiate patients with a different prognosis of the tumor’s clinical course. Prognostic criteria for CLL include time to disease progression and survival rates: (1) the low-risk group has either a normal karyotype of tumor cells or an isolated 13q deletion; (2) the intermediate-risk group is characterized by either an 11q deletion or trisomy 12; (3) the high-risk group is characterized by either a 17p deletion or a complex (composite) karyotype [4]. In addition, CLL heterogeneity is due to the multiplicity of the tumor cell clone sources [5]. At the time of diagnosis, approximately 10% of patients have a mutation in several key genes: NOTCH1, SF3B1, TP53, and ATM [6]. Recent studies have shown that CLL’s clinical course and outcome depend not only on genetic but also epigenetic factors [7].
MicroRNAs (miRNAs) are known to be involved in the regulation of numerous cellular processes associated with oncogenesis, including cell differentiation, proliferation, cell cycle regulation, and apoptosis [8]. The most common absent genomic region in CLL due to the key deletion is located on chromosome 13q14 and associated with the indolent form of the disease [9]. Calin et al. were among the first to report the role of miRNAs in tumorigenesis; they demonstrated that a cluster containing miR-15a and miR-16-1 is often deleted or downregulated in CLL and that these events correlate with the loss of the 13q14 allele [10]. Another study showed that miR-15a, miR-21, miR-34a, miR-155, and miR-181b are differentially expressed in CLL patients with del17p compared to those with a normal karyotype [11]. Aref et al. established an association between a high miR-29a expression level and poor prognostic markers in CLL [12]. The presence of del(13q) as a single aberration is associated with significantly lower miR-17 expression, as well as higher levels of miR-19a and miR-92a-1 compared to those in patients carrying unfavorable genetic aberrations [13]. Apparently, from a fundamental standpoint, miRNAs can be considered both elements of the molecular pathways involved in CLL development and clinical biomarkers.
The aim of this study is to identify the miRNA expression profile in CLL and determine the role of miRNAs in biological pathways associated with leukemogenesis in CLL.

2. Results

2.1. miRNA Expression Profile in Bone Marrow and Lymphatic Nodes in CLL

The expression levels of miRNAs -150, -20a, -26b, -34a, -451a, and -96 were analyzed by real-time RT-PCR in CLL and lymphadenopathy (LA) LN samples, as well as in CLL and non-cancerous blood disease (NCBD) BM samples. A more than three-fold difference in the expression level between the analyzed subgroups was considered significant.

2.1.1. Comparative Analysis of miRNA Expression Levels between Tumor Samples and Non-Cancerous Blood Diseases

We observed a statistically significant upregulation of miRNAs -34a, -26b, and miRNA-150 in CLL BM samples compared to NCBD samples (p < 0.05) (Table 1). The most significant, more than three-fold, upregulation in CLL BM samples was noted for miRNA-34a and miRNA-150 (p < 0.05). A comparative analysis of miRNA expression levels in LN samples demonstrated a statistically significant downregulation of miRNAs -20a, -26b, -34a, and miRNA-451a compared to LA (p < 0.05). The expression of miRNA-451a was decreased more than nine-fold in CLL LN samples (p < 0.05).

2.1.2. Comparative Analysis of miRNA Expression Levels between CLL BM Tumor Samples from Patients with Anemia and CLL Cases without Anemia

Using real-time RT-PCR, we analyzed the expression levels of miRNAs -150, -20a, -26b, -34a, -451a, and -96 in CLL BM samples with indications for therapy and anemia, CLL BM samples with indications for therapy without anemia, CLL BM samples without indications for therapy, and NCBD samples. The most significant changes in miRNA expression levels among all analyzed subgroups were noted for miRNA-150 and miRNA-34a (Figure 1). We noted a significant dynamic upregulation of miRNA-150 and miRNA-34a at various stages of tumor progression in CLL. The level of miRNA-150 was increased 10-fold in CLL without indications for therapy (p < 0.05), 25-fold in CLL with indications for therapy and without anemia (p < 0.05), and more than 48-fold in CLL with indications for therapy and in the presence of anemia (p < 0.05) compared to NCBD. The level of miRNA-34a was upregulated 2-fold in CLL without indications for therapy (p < 0.05), 4-fold in CLL with indications for therapy and without anemia (p < 0.05), and more than 10-fold in CLL with indications for therapy and in the presence of anemia (p < 0.05) compared to NCBD.

2.1.3. Comparative Analysis of miRNA Expression Levels between CLL BM Tumor Samples from Patients with Different Stages of CLL

A comparative analysis of miRNA expression levels was performed between groups of CM specimens with CLL of different malignancy grades. The stage of CLL was determined based on the Binet classification. The comparison groups comprised Stage A (n = 36), Stage B (n = 57), and Stage C (n = 21) CLL samples. The family-wise error rate (FWER) was assessed using the Bonferroni method to solve the multiple-hypothesis testing problem. A statistically significant rise in the expression levels of miRNA-150 and miRNA-34a with tumor progression was observed (p < 0.01) (Table 2). At the same time, no statistically significant differences in the expression levels of these miRNAs were observed when comparing Stage B and Stage C groups.

2.2. Bioinformatics Analysis of Pathways and Targets Associated with B-Cell Lymphomas

Using the miRPathDB2.0 resource, which is freely available at https://mpd.bioinf.uni-sb.de/ (accessed on 1 May 2024), for the analysis of target genes for miRNA-34a and miRNA-150, we identified target genes participating in hematopoiesis and biological processes involving lymphocytes (Table 3).
Next, we conducted a bioinformatics analysis of the miRNA target genes involved in KEGG cancer pathways. The list was obtained using the miRNet 2.0 resource (Figure 2). MiRNet is an miRNA-centric network visual analytics platform (https://www.mirnet.ca/miRNet/home.xhtml) (accessed on 10 May 2024).

3. Discussion

An analysis of the expression levels of miRNA-150, -20a, -26b, -34a, -451a, and -96 demonstrated a unique miRNA expression profile in CLL in BM and LN samples.
We observe a statistically significant ˃three-fold increase in expression levels of miRNA-34a and miRNA-150 in BM samples in CLL (p < 0.05) and a ˃three-fold decrease in miRNA-451a levels in CLL LN samples (p < 0.05). Numerous studies determined the miRNA-150 expression profile in lymphoid and myeloid cells, which indicate the involvement of miRNA-150 in the regulation of normal hematopoiesis [14]. Adams et al. showed that miRNA-150 overexpression impairs hematopoietic recovery in an experiment simulating the BM state after chemotherapy [15]. There are reports that miRNA-150 and miRNA-34a are regulators of lymphopoiesis [16,17]. Zhou et al. showed that aberrant expression of miRNA-150 leads to defects in B-cell development in BM [18]. Hu et al. demonstrated that the transcription factor FOXP1 plays a crucial role in early B-cell development [19]. Mraz et al. reported that GAB1 and FOXP1 are miRNA-150 targets [20]. Furthermore, Cerna et al. noted that miRNA-34a also inhibits FOXP1, limiting BCR signaling in CLL B cells [21]. Rao et al. also highlight that miRNA-34a impairs B-cell development by inhibiting the transcription factor Foxp1 [22]. A study by Xiao et al. showed that miRNA-150 regulates B-cell development and differentiation through inhibition of the transcription factor c-Myb [23]. However, Mraz et al. note no correlations between miRNA-150 and c-Myb levels in CLL samples [20]. A number of studies have shown that miRNA-34a expression in CLL depends on TP53 and, in particular, decreases in CLL patients carrying a 17p/TP53 deletion [24]. Cao et al. found that the miR-34a/MDM4/p53 pathway regulates apoptosis in CLL cells [25]. Taken together, these data highlight the role of miRNA-150 and miRNA-34a in the regulation of lymphopoiesis and pathogenesis of B-cell lymphomas.
A number of studies aimed at identifying not only the role of miRNAs in hematopoiesis but also the possibilities of using miRNAs as diagnostic and prognostic markers of B-cell tumors have been published to date [26]. Stamatopoulos et al. note that miRNA-150 upregulation in the serum of CLL patients is a marker of poor prognosis [27]. Selvam et al. demonstrated that miRNA-150 is a tumor suppressor and involved in cell cycle regulation [28]. Low miRNA-34e expression in CLL is associated with p53 inactivation and chemotherapy-resistant disease [29]. Richter’s syndrome (RS) is a complication in patients with CLL leading to the development of aggressive B-cell lymphomas; currently, there are no tests available to predict its onset. Balatti et al. showed that miRNA-125a and miRNA-34a can be valuable prognostic markers of RS and potentially provide clinicians with information indicating the optimal therapeutic strategy for patients with CLL [30]. Asslaber et al. note that a low miRNA-34a level is associated with shorter treatment-free survival rates in patients with CLL [31]. Gibcus et al. found that miRNA-150 expression is significantly higher in CLL compared to other B-cell lymphomas [32]. We note a similar trend of significant upregulation of miR-150 in BM samples in CLL (p < 0.05), which once again confirms the important contribution of miRNA in CLL pathogenesis. The bioinformatics analysis performed in our work revealed the involvement of miRNA-150 and miRNA-34a in cancer-associated biological pathways.
Anemia is a common clinical sign of a poor-prognosis disease in CLL patients [33]. We carried out a comparative analysis of miRNA levels between BM samples from CLL patients with indications for therapy in the presence anemia, BM samples from CLL patients with indications for therapy without anemia, and BM samples from CLL patients without indications for therapy. We showed that the miRNA-150 level is increased more than 40-fold (p < 0.05) in CLL patients with indications for therapy in the presence of anemia, more than 20-fold (p < 0.05) in CLL patients with indications for therapy without anemia, and about 10-fold (p < 0.05) in CLL patients without indications for therapy compared to NCBD BM samples. A similar picture of dynamic changes in miRNA expression levels is noted for miRNA-34a. For instance, the levels of miRNA-34a are two times higher in CLL with indications for therapy and in the presence of anemia compared to CLL with indications for therapy and without anemia. Chronic anemia develops in the presence of impaired BM function and a decreased number of new red blood cells [34]. A number of studies have shown that miRNA-150 participates in the regulation of erythropoiesis [35,36]. Dostalova Merkerova et al. found that miRNA-34a is differentially expressed in BM pathologies [37]. The role of miRNA-34a in the regulation of erythropoiesis still remains unknown. We observed a 10-fold increase in miRNA-34a expression levels in CLL patients with anemia (p < 0.05). Taken together, our results and data in the literature indicate that miRNA-150 and miRNA-34a are potent regulators of erythropoiesis. Further studies are required to identify their role in hematopoiesis.
We showed that a nine-fold downregulation of miRNA-451a is a characteristic trait of CLL LNs compared to LA (p < 0.05). Gu et al. demonstrated that BCL-2 is a target for miRNA-451, and upregulation of the latter contributes to enhanced apoptosis in breast cancer [38]. BCL-2 inhibitors have also been approved for the treatment of newly diagnosed and relapsed CLL [39]. Thus, miRNA-451a is a promising therapeutic target for inhibiting BCL2 in CLL. However, this hypothesis requires further studies.
We demonstrated that miRNA expression profiles differ between BM and LNs in CLL. This can be due to the fact that different samples were used in the studies, while different tumor microenvironments can be found in CLL [40]. Willimott et al. reported that CLL cells in tissues (BM and LNs) surrounded by the stroma exhibit a different pattern of miRNA expression compared to CLL cells circulating in the blood, which suggests an effect of the stroma on miRNA expression [41].
The discrepancy in miRNA expression profiles of bone marrow and lymph nodes may serve as an indication of myeloid cell abnormalities in bone marrow, potentially contributing to the development of anemia.
Based on the Human Disease Blood Atlas, six proteins (TCL1A, STC1, CD22, FCRL2, FCER2, CD6) have been identified as predictive markers for CLL [42]. At the same time, based on the miRPathDB 2.0 database, TCL1A, STC1, FCRL2, FCER2, and CD6 have been determined to be predicted targets for hsa-miR-150-5p, with TCL1A and STC1 being predicted targets for hsa-miR-34a-5p. These findings underscore the crucial role of miRNA-150 and miRNA-34a in biological pathways in CLL, indicating the necessity of further studies to experimentally verify these mRNA-miRNA interactions in CLL.
MiRNAs are important regulators that simultaneously have an effect on different biological pathways in CLL [24]. MiRNA expression can alter as a result of chromosomal changes, epigenetic modulations, and interactions with other genes. miRNAs are regulators of normal hematopoiesis and, apparently, their aberrant expression can contribute to the development of hematological tumors. Further research in this area will fundamentally expand the knowledge about the biological pathways underlying hematopoiesis. From a practical standpoint, the identification of correlations between miRNA expression profiles and the clinical data makes it possible to identify new biomarkers that will allow for the elaboration of personalized therapy for hematological tumors [43].
This study’s results may be influenced by the size of the study sample.

4. Materials and Methods

The study design is presented in the Figure 3.

4.1. Clinical Samples

The following samples were used in this study: (1) samples obtained by sternal puncture and aspiration biopsy of BM (n = 115). They included 49 cases of asymptomatic early-stage CLL with no indications for therapy and 66 cases of progressive CLL with an indication for therapy. The control group for the CLL BM samples consisted of patients with NCBDs (n = 35). (2) LN samples (n = 20) were collected from CLL patients. The control group for the CLL LN samples consisted of patients with LA (n = 37).
In envisioning the design of our study, we carefully considered the criteria for including patients with anemia in the CLL subgroup, imposing strict limitations. Upon conducting a preliminary examination, we have excluded all anemias that manifest with symptoms, including iron deficiency anemias, anemias caused by deficiencies in vitamin B-12 and folic acid, anemias resulting from erythropoietin deficiency, autoimmune hemolytic anemias, and other forms of hemolytic anemias, such as hereditary anemias. The purpose behind creating the CLL subgroup with anemia was to exclusively identify cases where normal erythropoiesis and/or myeloid hematopoiesis in bone marrow were suppressed by alternative mechanisms.
The characteristics of the groups are shown in Supplementary Table S1. Cytological and FFPE materials were obtained in compliance with Russian laws and regulations, written informed consent was obtained from each patient, and all of the data were depersonalized. Recruitment of the material for this study began on 10 January 2022and ended on 1 May 2024. This study was conducted in accordance with the Declaration of Helsinki and the study protocol No. 111 of 15 May 2018 was approved by the Ethics Committee of Novosibirsk State Medical University.

4.2. Isolation of Total RNA from Fine-Needle Aspiration Cytological Specimens

Each dried cytological specimen was washed in a microcentrifuge tube with three 200 μL portions of guanidine lysis buffer. Samples were vigorously mixed and incubated in a thermal shaker (BioSan, Riga, Latvia) at 65 °C for 15 min. Next, an equal volume of isopropanol was added. The solution was thoroughly mixed and kept at room temperature for 5 min. After centrifugation at 14,000× g for 10 min, the supernatant was decanted, and the pellet was washed with 500 μL of 70% ethanol and 300 μL of acetone. The resulting RNA was dissolved in 290 μL of deionized water.

4.3. Isolation of Total RNA from FFPE

A total of 1 mL of mineral oil was added to a tube containing three 15 μm paraffin-embedded sections of lymph node tissue for deparaffinization. The tube was then vortexed for 10 s and incubated in a thermoshaker (BioSan, Riga, Latvia) at 65 °C and 1300 rpm for 2 min. Next, samples were centrifuged at 13,000–15,000× g for 4 min. The supernatant was removed without disrupting the precipitate. A total of 1 mL of 96% ethanol was added to the precipitate followed by vortexing for 10 s and centrifugation at 13,000–15,000× g for 4 min. The supernatant was removed without disrupting the precipitate, followed by the addition of 1 mL of 70% ethanol and centrifugation at 13,000–15,000× g for 2 min. The resulting precipitate was further used for nucleic acid isolation. A total of 600 µL of guanidine lysis buffer was added to each sample and total RNA was isolated as described above.

4.4. miRNA Selection

miRNAs involved in lymphocyte development and differentially expressed in non-Hodgkin lymphomas were selected for analysis based on data in the literature [26,44]. A total of 7 miRNAs were studied: miRNAs -20a-5p, -96-5p, -26b-5p, -34a-5p, -150-5p, and -451a. The geometric mean of the Ct values of three miRNAs (-378-3p, -191-5p, and -103a-3p), which were selected based on our previous data [45], was used for normalization. The sequences of oligonucleotides for reverse transcription and PCR are presented in Supplementary Table S2. All oligonucleotides were synthesized by Vector-Best (Novosibirsk, Russia). Oligonucleotides were selected using the PrimerQuest tool (https://eu.idtdna.com/) (accessed on 1 May 2020). The E value varied within the 92.5–99.7% range depending on the system used.

4.5. Reverse Transcription

For cDNA synthesis, reverse transcription was performed in a volume of 30 μL. The reaction mixture contained 3 μL of the RNA sample and RT buffer solution with RT primers (Vector-Best, Novosibirsk, Russia). The total RNA concentration was within the range of 115–150 ng/μL; optical density 260/280 and 260/230 ratios were ≥1.9 and ≥1.5, respectively. The reaction mixture was incubated at 16 °C for 15 min and then at 42 °C for 15 min, followed by heat inactivation at 95 °C for 2 min.

4.6. Real-Time PCR

MicroRNA expression was assessed by real-time PCR using a CFX96 detection system (Bio-Rad Laboratories, Hercules, CA, USA). The total volume of each reaction mixture was 30 μL; the reaction mixture contained 3 μL of cDNA, 1× PCR buffer (Vector-Best, Novosibirsk, Russia), 0.5 μL of each primer, and 0.25 μL of a dual-labeled probe. The PCR protocol was as follows: incubation at 50 °C for 2 min, pre-denaturation at 94 °C for 2 min, followed by 50 cycles of denaturation (94 °C for 10 s), annealing, and extension (60 °C for 20 s).

4.7. Statistical Analysis

The statistical analysis was performed using Statistica v13.1 software. The Mann–Whitney U test was used. p values < 0.01 were considered statistically significant.
The bioinformatics analysis of miRNA target genes was performed using the miRNet 2.0 tool (https://www.mirnet.ca/miRNet/home.xhtml) (accessed on 10 May 2024).

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/lymphatics2030013/s1, Table S1: Patient characteristics at the time of diagnosis; Table S2: The oligonucleotide sequences used in this study.

Author Contributions

Y.A.V. contributed to the conception and design of the work, performed data collection, and wrote the manuscript draft. S.E.T., P.S.D., S.S.F. and Y.Y.S. contributed to the conception and design of the work, participated in the experiments and data analysis, and wrote the manuscript draft. I.B.K., S.S.F. and Y.Y.S. collected clinical samples. Y.A.V. and S.A.D. conducted the experiments. T.I.P. and I.F.Z. contributed to the conception and design of the work, supervised this study, and reviewed and edited the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This work is supported by grants from the Russian Science Foundation (project No. 20-14-00074-P).

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of Novosibirsk State Medical University, study protocol No. 15 of 25 May 2020.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

All data generated or analyzed during this study is available with the corresponding author (RSR) and will be provided on request.

Acknowledgments

The cell analysis was carried out at the Center for Collective Use of Microscopic Research at the Institute of Cytology and Genetics SB RAS (supported by the IC&G budget project). The authors express their gratitude to the Center for Collective Use (CCU) “Bioinformatics” for the computational resources and their software, created within the framework of the budget project FWNR-2022-0020.

Conflicts of Interest

The authors declare no conflict of interest. Sergei E. Titov is Employed by AO Vector-Best Ltd. The company had no role in the design, collection, analyses, or interpretation of data, the writing of the manuscript, or the decision to publish the results.

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Lymphatics 02 00013 g001
Figure 1. A comparative analysis of miRNA expression levels in chronic lymphocytic leukemia without indications for therapy (CLL (T−)), with indications for therapy and without anemia (CLL (T+) (A−)), with indications for therapy and anemia (CLL (T+) (A+)), and non-cancerous blood diseases (NCBDs): (A) miRNA-34a; (B) miRNA-150. The median value, upper and lower quartiles, non-outlier range, and outliers indicated by circles are presented in the figure. Horizontal lines connecting boxes in pairs indicate statistically significant differences between the compared subgroups. Asterisks denote statistically significant differences at p < 0.05.
Figure 1. A comparative analysis of miRNA expression levels in chronic lymphocytic leukemia without indications for therapy (CLL (T−)), with indications for therapy and without anemia (CLL (T+) (A−)), with indications for therapy and anemia (CLL (T+) (A+)), and non-cancerous blood diseases (NCBDs): (A) miRNA-34a; (B) miRNA-150. The median value, upper and lower quartiles, non-outlier range, and outliers indicated by circles are presented in the figure. Horizontal lines connecting boxes in pairs indicate statistically significant differences between the compared subgroups. Asterisks denote statistically significant differences at p < 0.05.
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Figure 2. Target analysis of miRNA-34a and miRNA-150 using miRnet 2.0. Green diamonds indicate microRNAs, red diamonds indicate their target genes.
Figure 2. Target analysis of miRNA-34a and miRNA-150 using miRnet 2.0. Green diamonds indicate microRNAs, red diamonds indicate their target genes.
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Figure 3. A schematic representation of the experimental design and workflow of the microRNA analysis. Total RNA was isolated from fine-needle aspiration cytological specimens of bone marrow and paraffin-embedded sections of lymph node tissue. Subsequently, miRNA expression levels were evaluated using real-time PCR. Then, target genes involved in hematopoiesis, lymphocyte differentiation, and cancer pathways were analyzed using bioinformatics methods.
Figure 3. A schematic representation of the experimental design and workflow of the microRNA analysis. Total RNA was isolated from fine-needle aspiration cytological specimens of bone marrow and paraffin-embedded sections of lymph node tissue. Subsequently, miRNA expression levels were evaluated using real-time PCR. Then, target genes involved in hematopoiesis, lymphocyte differentiation, and cancer pathways were analyzed using bioinformatics methods.
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Table 1. Comparative analysis of miRNA expression levels between CLL and non-cancerous samples.
Table 1. Comparative analysis of miRNA expression levels between CLL and non-cancerous samples.
Bone MarrowLymph Node
Fold Changep-ValueFold Changep-Value
miR-20a1.08NS−1.932 × 10−5
miR-961.14NS−2.84NS
miR-26b2.201 × 10−17−2.585 × 10−5
miR-34a4.341 × 10−7−1.882 × 10−2
miR-15018.981 × 10−22−1.05NS
miR-451a−1.07NS−9.224 × 10−4
NS—not significant.
Table 2. Comparative analysis of miRNA expression levels between CLL BM tumor samples from patients with different stages of CLL.
Table 2. Comparative analysis of miRNA expression levels between CLL BM tumor samples from patients with different stages of CLL.
miRNAStage B vs. Stage AStage C vs. Stage BStage C vs. Stage A
Fold ChangeAdjusted
p-Value		Fold ChangeAdjusted
p-Value		Fold ChangeAdjusted
p-Value
miR-20a−1.02NS1.02NS1NS
miR-96−1.41NS1.15NS−1.22NS
miR-26b−1.02NS1.12NS1.09NS
miR-34a1.83 × 10−31.33NS2.392 × 10−3
miR-1502.731 × 10−31.69NS4.621 × 10−5
miR-451a−1.32NS−1.15NS−1.52NS
NS—not significant.
Table 3. The biological pathways involved in hematopoiesis and lymphocyte differentiation with participation of the miRNAs under study. The list was generated using the miRPathDB 2.0 tool.
Table 3. The biological pathways involved in hematopoiesis and lymphocyte differentiation with participation of the miRNAs under study. The list was generated using the miRPathDB 2.0 tool.
miRNAPathwayp-ValueTargets
miR-150hematopoiesis0.018CCR6, CREB1, EP300, FLT3, MMP14, MYB, PRKCA, STAT1, STAT5B, TP53, VEGFA, ZEB1
lymphocyte differentiation0.018CCR6, EP300, FLT3, MMP14, MYB, STAT5B, TP53, ZEB1
lymphocyte activation0.036CCR6, EP300, FLT3, MMP14, MYB, P2RX7, STAT5B, TP53, ZEB1
positive regulation of lymphocyte apoptotic process0.047P2RX7, TP53
miR-34ahematopoiesis0.027ATG5, AXL, BAX, BCL2, CDK6, CSF1R, DLL1, ERBB2, FOS, FOXP1, HDAC1, HMGB1, IFNB1, JAG1, KIT, KLF4, LEF1, MYB, MYC, NOTCH1, NOTCH2, SIRT1, TCF7, TP53, TREM2, WNT1, ZAP70
microRNA pathway associated with chronic lymphocytic leukemia0.002BCL2, TP53, ZAP70
lymphocyte activation0.006AKT1, ATG5, AXL, BAX, BCL2, CD24, CD44, CDK6, DLL1, ERBB2, FKBP1B, FLOT2, FOXP1, HMGB1, IFNB1, IMPDH2, KIT, LEF1, MYB, NOTCH2, PIK3CG, SRC, TCF7, TP53, ULBP2, WNT1, ZAP70
lymphocyte differentiation0.010ATG5, AXL, BAX, BCL2, CDK6, DLL1, ERBB2, FOXP1, HMGB1, IFNB1, KIT, LEF1, MYB, NOTCH2, TCF7, TP53, WNT1, ZAP70
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Veryaskina, Y.A.; Titov, S.E.; Kovynev, I.B.; Pospelova, T.I.; Fyodorova, S.S.; Shebunyaeva, Y.Y.; Demakov, S.A.; Demenkov, P.S.; Zhimulev, I.F. MicroRNA: A Signature for the Clinical Progression of Chronic Lymphocytic Leukemia. Lymphatics 2024, 2, 157-167. https://doi.org/10.3390/lymphatics2030013

AMA Style

Veryaskina YA, Titov SE, Kovynev IB, Pospelova TI, Fyodorova SS, Shebunyaeva YY, Demakov SA, Demenkov PS, Zhimulev IF. MicroRNA: A Signature for the Clinical Progression of Chronic Lymphocytic Leukemia. Lymphatics. 2024; 2(3):157-167. https://doi.org/10.3390/lymphatics2030013

Chicago/Turabian Style

Veryaskina, Yuliya A., Sergei E. Titov, Igor B. Kovynev, Tatiana I. Pospelova, Sofya S. Fyodorova, Yana Yu. Shebunyaeva, Sergei A. Demakov, Pavel S. Demenkov, and Igor F. Zhimulev. 2024. "MicroRNA: A Signature for the Clinical Progression of Chronic Lymphocytic Leukemia" Lymphatics 2, no. 3: 157-167. https://doi.org/10.3390/lymphatics2030013

APA Style

Veryaskina, Y. A., Titov, S. E., Kovynev, I. B., Pospelova, T. I., Fyodorova, S. S., Shebunyaeva, Y. Y., Demakov, S. A., Demenkov, P. S., & Zhimulev, I. F. (2024). MicroRNA: A Signature for the Clinical Progression of Chronic Lymphocytic Leukemia. Lymphatics, 2(3), 157-167. https://doi.org/10.3390/lymphatics2030013

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