The miRNA content of circulating exosomes in DLBCL patients and in vitro influence of DLBCL-derived exosomes on miRNA expression of healthy B-cells from peripheral blood

Abstract

BACKGROUND:

Due to the heterogeneous nature of Diffuse Large B-cell Lymphoma (DLBCL), the mechanisms underlying tumor development and progression have not yet been fully elucidated.

OBJECTIVE:

This study aimed to compare the characteristics of plasma exosomes of DLBCL patients and healthy individuals and to evaluate the exosomal interactions between DLBCL cell lines and normal B-cells.

METHODS:

Exosome isolation was performed using an ultracentrifugation-based protocol from plasma of 20 patients with DLBCL and 20 controls. The expression of miRNAs from exosome samples was analyzed using a miRNA expression microarray. The presence of exosome-mediated communication between the lymphoma cells and normal B-cells was determined by the co-culture model.

RESULTS:

A significant increase in plasma exosome concentrations of DLBCL patients was observed. There was also a significant decrease in the expression of 33 miRNAs in plasma exosomes of DLBCL patients. It was determined that normal B-cells internalize DLBCL-derived exosomes and then miRNA expression differences observed in normal B-cells are specific to lymphoma-subtypes.

CONCLUSIONS:

MiR-3960, miR-6089 and miR-939-5p can be used as the miRNA signature in DLBCL diagnosis. We suppose that the exosomes changed the molecular signature of the target cells depending on the genomic characterization of the lymphoma cells they have originated.

Keywords

Diffuse large B-cell lymphoma exosomes miRNA B-cells cellular uptake

1. Introduction

Diffuse Large B-cell Lymphoma (DLBCL) accounts for about 30–40% of Non-Hodgkin’s lymphomas (NHLs). Although there is no detailed data on the incidence of DLBCL in Turkey, NHL ranks the eighth and seventh most common cancer in women and man, respectively [1]. DLBCL is highly heterogeneous in terms of genetic, immunological, morphological, and clinical features [2, 3]. New biomarkers that will provide insight into disease diagnosis, prognosis, and response to therapy are needed since the analyzes which are used to classified into subtypes in routine clinical practice do not meet all the biological parameters.

Circulating miRNAs have many characteristics of ideal biological markers such as stability, being tightly conserved among species, and being different according to the tissue or clinical stage [4, 5]. In recent years, especially in the diagnosis and classification of cancer, the superiority of exosomal miRNA profiles as biomarkers has been emphasized [6, 7, 8]. There are limited data on exosomal miRNA profiles and their roles in the diagnosis and pathogenesis of DLBCL.

Exosomes that have changed the image of “cellular garbage collectors” to “information-carrying vesicles” over time, play an active role in intercellular communication. Exosomal cargo compositions are considered as a fingerprint of originating cells and transferred to the target cells [9, 10]. There are limited studies on the internalization of lymphoma-derived exosomes by peripheral blood cell populations [11, 12]. The common finding in these studies is that B-cells effectively internalize lymphoma-derived exosomes, but the effects of exosomes after internalization by target B cells are not yet known.

In this study, we aimed to (i) compare exosomal miRNA expression profiles in DLBCL patients and healthy individuals, and (ii) determine whether DLBCL-derived exosomes are mediators that transfer miRNA-specific information to normal B-cells.

2. Materials and methods

2.1 The study group

The minimum number of samples was calculated (http://bioinformatics.mdanderson.org/MicroarraySam pleSize/). Twenty patients who applied to the Hematology Clinic, Pamukkale University between June 2015 and February 2016 were evaluated. The inclusion criteria were as follows: 1) newly diagnosed and histopathologically proven de novo DLBCL, 2) between 18 to 80 years old, 3) written informed consent to participate in the study. The exclusion criteria were: 1) use of cytotoxic agents, 2) pre-existing HIV or active EBV infections (In situ hybridization for EBV encoded small nuclear RNAs-EBERs- was used to exclude active EBV infection). The immunophenotype subgroups were routinely determined using the algorithm defined by Hans et al., and the patients were divided into two immunophenotypic subgroups: Germinal Center (GC) and Non-Germinal Center (Non-GC) [3].

Since gender is not considered as a risk factor for DLBCL in the literature, 20 voluntary healthy individuals who matched the patients’ ages were selected as the control group. For the group, inclusion criteria included no prior cancer history, no chronic and autoimmune disease history, age between 18 and 80, and no previously receiving cytotoxic drug treatment.

This study was approved by the Institutional Ethics Committee, Pamukkale University (Approval no: 14, Approval date: 27.08.2013), and written informed consent was provided by all participants.

2.2 Exosome isolation from plasma samples

Peripheral blood sample collection was performed as previously described [13, 14]. Briefly, venous blood sample (10 ml) were taken through a $\geqslant$ 21-gauge-needle placed in the right arm of each patient into EDTA-coated tubes (Vacutainer K2EDTA tube, BD) at 9:00 am, on the day the patient was hospitalized and the first 2 ml of blood was discarded. The following steps were undertaken for each individual sample. Exosome isolation from plasma samples was carried out in 2 steps: In the first step, the aim was to obtain a platelet-free plasma sample, and centrifugation was twice carried out consecutively at 2,500 $\times$ g for 15 minutes. In the second step, the samples were filtered through a 0.2 $\mu$ m pore diameter filter after centrifugation at 12,000 $\times$ g for 45 minutes, and two consecutive ultracentrifugation processes were performed at 110,000 $\times$ g for 2 hours and 1 hour (Optima Max-XP, Beckman Coulter). After centrifugation, the pellet was diluted with PBS and 20 $\mu$ l of the sample was directly sent to the Electron Microscope Unit. The remaining samples were stored at $-$ 80 ${}^{\circ}$ C for further analysis.

Exosome concentrations were estimated using a commercial kit based on the measurement of acetylcholinesterase enriched activity in exosomes (Exocet, SBI).

2.3 Characterization of isolated exosomes

2.3.1 Morphological characterization

To characterize and visualize exosome morphology, scanning transmission electron microscopy (STEM) and scanning electron microscopy (SEM) were used. Briefly, a 5- $\mu$ L aliquot from the fresh exosome suspension was transferred to formvar-coated nickel grid and fixed by 2% paraformaldehyde and 1% glutaraldehyde. After washing with distilled water, the grids were treated with 2% uranly acetate and visualized by Field Emission SEM (FESEM-Carl Zeiss, Supra 40 VP) containing a STEM detector. In SEM, the exosome pellet was dipped onto a poly-L lysine-coated slide and fixed with 2.5% glutaraldehyde and 4% paraformaldehyde. After washing with distilled water, the slide was coated with gold/palladium (Au/Pd) and analyzed by Field Emission SEM (FESEM-Carl Zeiss, Supra 40 VP).

2.3.2 Determination of total protein concentration in the exosome samples

Exosomal protein lysates were prepared in the lysis buffer (Cell Signalling Tech.), including protease inhibitor cocktail (Cell Signalling Tech.) and EDTA (Sigma). The lysates were used in determining total protein amounts, imaging total proteins by SDS-PAGE, and Western Blot analysis.

Total protein amounts of exosomes were determined by the Bradford method (DC Protein Assay, BioRad, Protein Standard II, BSA, BioRad).

2.3.3 Detection of exosomal marker proteins

According to the MISEV2014 guidelines, we checked the expression of CD63, CD81, and TSG101 as exosomal protein markers by western blot [14]. Western blot analyzes were completed using anti-CD63 (ab68418-Abcam), anti-CD81 (ab155760-Abcam), anti-TSG101 (ab30871-Abcam), anti- $\beta$ actin (ab75186-Abcam) primary antibodies, and HRP-conjugated secondary antibody (ab97069-Abcam).

2.4 Exosomal total RNA extraction

Before total RNA isolation, exosome samples were treated with RNase A (Invitrogen) in order to avoid external RNA contamination. Total RNA isolation was completed using Trizol reagent (Invitrogen). Briefly, 100 $\mu$ l lysis buffers (Qiagen) and 1 mL Trizol (Roche) were added on 300 $\mu$ L of exosome samples. After the addition of chloroform (Sigma), the aqueous phase was separated, and RNA precipitation was performed with isopropyl alcohol (AppliChem) and 70% ethanol (Sigma). The quantity and quality of RNA were assessed by NanoDrop (Thermo Scientific) and Agilent 2100 Bioanalyzer (Agilent Technologies).

2.5 Co-culture model

2.5.1 B-cell isolation from peripheral blood mononuclear cells

Due to the increased exosome internalization capacity in B-cells with age, a 5-ml peripheral blood sample was taken from a 62-year-old healthy individual [15]. B-cells were isolated by negative selection (MACS Human B Cell Isolation Kit II, Miltenyi Biotec) and analyzed on a flow cytometer (Beckman Coulter).

The B-cells were cultured in RPMI-1640 (Gibco, Life Technologies), supplemented with 10% exosome-depleted Fetal Bovine Serum (FBS) (Gibco, Life Technologies) and 1% penicillin/streptomycin (Gibco, Life Technologies) at 37 ${}^{\circ}$ C in a humidified atmosphere with 5% CO ${}_{2}$ . The exosome-depleted FBS were obtained by overnight ultracentrifugation at 120,000 xg (Optima Max-XP, Beckman Coulter) [16]. The medium and conditions were applied to all cells used in the study.

2.5.2 DLBCL cell lines and culture conditions

A total of 5 cell lines belonging to different DLBCL subtypes were used: Pfeiffer (CRL-2631, ATCC) and SU-DHL-4 (CRL-2957, ATCC) for the GC B cell-like (GCB), SU-DHL-2 (CRL-2956, ATCC) and U2932 (ACC 633, DSMZ) for the activated B cell-like (ABC), and U2940 (ACC 634, DSMZ) for the primary mediastinal B-cell lymphoma (PMBL) subtype. All cell lines were obtained from the Leibnitz Institute DSMZ-German Collection of Microorganisms and Cell Cultures (www.dsmz.de).

Before the co-culture experiment, the exosome isolation was performed on normal B-cells and all of the lymphoma cell lines as previously described. In the co-culture model, 6-well cell culture dishes (Greiner Bio-One) were used, and the lymphoma cells were added to each well at a concentration of 1 $\times$ 10 ${}^{6}$ /ml. Then, an insert (Greiner Bio-One) containing a membrane with 0.4- $\mu$ m pore size was placed, and normal B-cells at the concentration of 1 $\times$ 10 ${}^{6}$ /ml were added to the insert. After 24 h incubation, the microarray analysis performed on the total RNA isolated from the cells over the insert to demonstrate the transfer of the lymphoma-derived exosomes to normal B-cells.

Figure 1.

STEM and TEM images of exosomes isolated from plasma samples of a healthy individual and a DLBCL patient. A-1: STEM (Magnification: 125.00 K X, Scale bars: 200 nm) and A-2: TEM image (Magnification: 67.00 K X, Scale bars: 200 nm) of exosomes in a healthy individual. B-1: STEM (Magnification: 100.00 K X, Scale bars: 200 nm) and B-2: TEM image (Magnification: 50.00 K X, Scale bars: 200 nm) of exosomes in a patient. This figure also shows that patient’s plasma contains more particles than a healthy individual. Pa: target particle, PaR: particle diameter by point to point measure.

2.6 Microarray analysis

miRNA microarray analysis was performed using SurePrint G3 Human miRNA r21 Array Kit (Agilent Technologies). The labeling, hybridization, and washing procedures were performed according to the manufacturer’s instructions. Each sample was repeated three times and multiple correlation analyzes were completed by taking the mean values. For validation of the microarray data, differentially expressed miRNAs (down-regulated: hsa-miR-3960, hsa-miR-6089, hsa-miR-939-5p, hsa-miR-1207-5p, hsa-miR-595; up-regulated: miR-6803-5p) were investigated by real-time-PCR using the miRCURY LNA ${}^{\text{TM}}$ Universal RT MicroRNA PCR kit (Exiqon, Germany). Real-time PCR was carried out on a Light Cycler 2.0 instrument (Roche Diagnostics). The expression levels of miRNAs were normalized to U6 RNA and the relative expression levels were calculated using the 2- $\Delta\Delta$ Ct method. All the samples were repeated three times for each miRNA.

Table 1
Association between plasma exosome concentration, total exosomal protein concentration and clinicapathological variables in DLBCL patients

Variable

No. of patients (%)

Exosome

concentration

(10

{}^{10}

/ml plasma)

p

value

Exosomal protein

concentration

(

\mu

g/100 ml plasma)

p

value

Immunophenotype

Germinal Center (GC)

7 (35)

18.28

\pm

3.91

0.430

123.81

\pm

102.85

0.028

Non-GC

13 (65)

27.98

\pm

20.59

278.47

\pm

186.9

Stage

Early (I-II)

4 (20)

24.38

\pm

10.01

0.682

290.0

\pm

206.97

0.494

Advanced (III-IV)

16 (80)

24.64

\pm

18.8

207.93

\pm

171.55

IPI score

Low (0–2)

6 (30)

35.41

\pm

15.86

0.170

282.07

\pm

62.14

0.291

High (3–5)

14 (70)

25.42

\pm

20.82

160.55

\pm

177.24

Tumor location

Nodal

12 (60)

18.4

\pm

4.16

0.208

240.33

\pm

199.77

0.633

Extranodal

8 (40)

33.87

\pm

24.69

200.35

\pm

143.88

*: Significant $p$ values are shown in bold and italic.

Figure 2.

(A) Analysis of the total protein content of exosomes isolated from 8 healthy individuals (Left) and 8 DLBCL patients (Right) by SDS-PAGE gel stained with Coomassie blue. MWM: Molecular weight marker (10–250 kDa) (Thermo Sci.). (B) Representative western blot image showing the expression of CD63, CD81, TSG101, and $\beta$ -actin proteins in the plasma exosomes of 9 DLBCL patients. The expected size of the corresponding proteins is given on the right side. $\beta$ -actin protein expression was not detected in only three exosome samples (line 1, 2, and 9).

2.7 Statistical analysis

Statistical analysis was performed using the SPSS (version 17.0; SPSS Inc., Chicago, IL, USA) software. Data represented as mean $\pm$ SD. Differences between the groups were compared by t-test while the Mann-Whitney U test was used to compare exosome concentration, exosomal protein concentration and clinicopathological parameters in DLBCL patients. The Cox regression analysis was used to determine the association between overall survival and the selected variables. Analysis of microarray data was employed with GeneSpring GX software version 14.9 (Agilent Technologies, CA, USA). Fold change filter was set to two-fold, and then unpaired $t$ -test was used to identify significant gene expression changes ( $p<$ 0.05) with multiple testing corrections (Bonferroni and Benjamini-Hochberg). Pathway analysis was performed using the KEGG (Kyoto Encyclopedia of Genes and Genomes) database.

Table 2
Downregulated miRNAs in the plasma exosomes isolated from DLBCL patients

miRNA	Sequence	Accession number	Fold change
hsa-miR-181b-5p	ACCCACCGACAGCA	MIMAT0000257	16.15
hsa-miR-181d-5p	ACCCACCGACAACAATG	MIMAT0002821	16.10
hsa-miR-197-5p	CCTCCCACTGCCC	MIMAT0022691	25.77
hsa-miR-432-5p	CCACCCAATGACCTACTC	MIMAT0002814	7.51
hsa-miR-595	AGACACACCACGGCACA	MIMAT0003263	7.88
hsa-miR-623	ACCCAACAGCCCCTGC	MIMAT0003292	6.84
hsa-miR-937-5p	CCAGCCCCACCC	MIMAT0022938	22.02
hsa-miR-939-5p	CACCCCCAGAGCC	MIMAT0004982	56.55
hsa-miR-1207-5p	CCCCTCCCAGCCT	MIMAT0005871	57.02
hsa-miR-1268a	CCCCCACCACCAC	MIMAT0005922	53.14
hsa-miR-1268b	CACCCCCACCACC	MIMAT0018925	58.80
hsa-miR-1307-3p	CACGACCGACGCC	MIMAT0005951	10.70
hsa-miR-1587	CCCAACCCAGCCC	MIMAT0019077	16.95
hsa-miR-2861	CCGCCCACCGC	MIMAT0013802	11.08
hsa-miR-3656	CCACCCCCGCAC	MIMAT0018076	31.36
hsa-miR-3960	CCCCCGCCTCCG	MIMAT0019337	98.68
hsa-miR-4481	AACCACCAGCCCAC	MIMAT0019015	12.47
hsa-miR-4632-5p	TCCGCCACACCCA	MIMAT0022977	8.34
hsa-miR-4701-3p	ACACCACACCCATCAC	MIMAT0019799	14.47
hsa-miR-4707-5p	CCAGAACCCGCCC	MIMAT0019807	5.69
hsa-miR-4721	CCACCGTCACCTGG	MIMAT0019835	4.62
hsa-miR-4725-3p	CCCGACACTGACGC	MIMAT0019844	4.90
hsa-miR-4741	AGCCGACCCCTCC	MIMAT0019871	27.30
hsa-miR-4763-3p	CCCGCCCAGCAC	MIMAT0019913	17.14
hsa-miR-6089	CCGCCCCGCCC	MIMAT0023714	76.72
hsa-miR-6127	CCTCCCACCCACTC	MIMAT0024610	19.64
hsa-miR-6724-5p	CCCCACGCCCG	MIMAT0025856	25.24
hsa-miR-6803-5p	ACGCCCAGCCCC	MIMAT0027506	6.36
hsa-miR-6840-3p	CACCCCGCACAAAG	MIMAT0027583	16.11
hsa-miR-7108-5p	CCACCCGCCTGC	MIMAT0028113	17.08
hsa-miR-7845-5p	CCACGACCCTCCC	MIMAT0030420	16.46
hsa-miR-8069	ACGCCGACCGCC	MIMAT0030996	5.24
hsa-miR-8071	CCACCCACTCCAGT	MIMAT0030998	18.51

3. Results

3.1 Characteristics of the patients with DLBCL

The mean age at diagnosis was 62.5 $\pm$ 15.12 years for DLBCL patients, while the mean age of the healthy controls was 55.6 $\pm$ 14.00 ( $p=$ 0.108). Demographic and clinical data of the patients are given in Table 1.

Table 3
KEGG pathway analysis and proposed target genes for the deregulated miRNAs

KEGG pathway	miRNA	Proposed target genes
Metabolic	hsa-miR-3960/ hsa-miR-939	CERS1, GPAT4, PHOSPHO1, NDUFS7, AC02,
	hsa-miR-3960	MIF, GPLS
	hsa-miR-939	CEL, AK8, TYMP, ALOX12B, HPD, CKMT1A, GPAA1,
Signalling pathways in cancer (Rab1, PI3K, Ras, cAMP, PPAR, MAPK, mTOR, Wnt)	hsa-miR-3960/ hsa-miR-939	COL6A2, SIPA1L3, MAPK8IP3, GNAI2, PPP2R3B, GRIN1, APOA1, PI3R2, PLIN1, FXD1, PRKCG, MAP2K7, CACNG7, HCN2, SRF, SSTR5, WNT6,
Signalling pathways in cancer (cAMP, cGMP, MAPK)	hsa-miR-939	GRP119, CACNA1F
Transcriptional misregulation in cancer	hsa-miR-3960/ hsa-miR-939	MLLT1
Endocytosis	hsa-miR-3960/ hsa-miR-939	AP2A2, DNM2, GRK6, CYTH2
Ribosome biogenesis	hsa-miR-939	MRPL21, RPL24, RPLP2, RPS11
Ubiquitin mediated proteolysis	hsa-miR-3960/ hsa-miR-939	HUWE1, UBE2O
Protein digestion and absorption	hsa-miR-3960/ hsa-miR-939	SLC7A8
	hsa-miR-3960	SLC9A3
	hsa-miR-939	CTRB1
Mitophagy	hsa-miR-3960/ hsa-miR-939	TBC1D17
	hsa-miR-939	FIS1
Ferroptosis	hsa-miR-3960/ hsa-miR-939	MAP1LC3B
Necroptosis	hsa-miR-3960	HIST3H2A

Figure 3.

(A) Heat-map representation of expression profiles for the differentially expressed miRNA in the plasma exosome samples of DLBCL patients. The color bar shows the color contrast level of the heat map. Red and blue indicate high and low expression levels, respectively. (B) Cluster analysis based on deregulated miRNAs in the plasma exosome samples of DLBCL patients. Each row represents one exosome sample from patient 1 through 20 and each column represents one miRNA. The color bar shows the color contrast level of the heat map. Red and blue indicate high and low expression levels, respectively.

Figure 4.

Deregulated miRNAs in DLBCL cell-derived exosomes in comparison with normal B cell-derived exosomes before and after co-culture experiments. Cell lines were divided into two groups according to cell of origin as GC (Pfeiffer and SU-DHL-4) (A) and non-GC cell lines (SU-DHL-2, U2932, and U2940) (B). Venn diagrams show deregulated miRNAs isolated from the cell line-derived exosomes before (left) and after (right) co-culture experiments. Upregulated miRNAs are shown in red and downregulated miRNAs in blue. *: Upregulated in Pfeiffer cell-derived exosomes, downregulated in SU-DHL-4 cell-derived exosomes; **: Upregulated in normal B cells co-cultured with U2940 cells, downregulated in normal B cells co-cultured with SU-DHL-2 and U2932 cells.

3.2 Plasma exosome concentrations and characterizations in healthy individuals and DLBCL patients

Plasma exosome concentrations of healthy individuals and the patients are 4.35 $\times$ 10 ${}^{10}$ $\pm$ 2.89/ml (range 1.84–8.17 $\times$ 10 ${}^{10}$ /ml) and 24.59 $\times$ 10 ${}^{10}$ $\pm$ 17.17/ml (range 13.18–86.28 $\times$ 10 ${}^{10}$ /ml), respectively ( $p=$ 0.0001). The relation between exosome concentrations and clinicopathological characteristics of the patients were summarized in Table 1.

The STEM and SEM analyses showed that exosomes isolated from healthy individuals and DLBCL patients were between 40–120 nm diameter range as expected (Fig. 1). Exosomal total protein concentrations in healthy individuals and DLBCL patients were 65.72 $\pm$ 19.86 $\mu$ g/100 ml plasma (range 53.22–98.89 $\mu$ g/100 ml) and 224.34 $\pm$ 176.43 $\mu$ g/100 ml plasma (range 99.66–575.29 $\mu$ g/100 ml), respectively ( $p=$ 0.001). Figure 2A shows the SDS-PAGE analysis of the representative exosome samples isolated from healthy individuals and DLBCL patients. The exosomal protein concentrations were compared with the demographic characteristics of the patients (Table 1). Exosomes isolated from healthy individuals were positive for CD63, CD81, TSG101, and $\beta$ -actin. In DLBCL patients, all exosome samples carried the marker proteins of CD63, CD81, and TSG101, although exosomes belonging to 3 patients (patients 1, 2, and 9) did not contain $\beta$ -actin protein (Fig. 2B).

The patients received standard chemotherapy with R-CHOP. Eight of the patients died within the observation period and the mean overall survival time was 32.25 months (range 1–63 months). The exosome concentration and the exosomal protein concentration were not statistically associated with overall survive time (HR: 0.967, 95% CI: 0.895–1.044, $p=$ 0.387; HR: 0.996, 95% CI: 0.991–1.001, $p=$ 0.102, respectively).

3.3 Identification of miRNAs present in plasma-derived exosomes

Compared to healthy individuals, a statistically significant decrease was observed in the expression of 33 miRNAs in DLBCL patients according to the Bonferroni multiple correlation analysis (Table 2) (Fig. 3A). When the Benjamini-Hochberg correlation analysis was applied, we found that 3 miRNAs (hsa-miR-3960, hsa-miR-6089, and hsa-miR-939-5p) were significantly down-regulated in the plasma exosomes of DLBCL patients ( $p=$ 0.00067, $p=$ 0.00377 and $p=$ 0.00411, respectively). The hierarchical cluster analysis of the microarray data is also given in Fig. 3B. Since hsa-miR-6089 cannot be found in the miRNA-target databases, only the target genes and pathways of hsa-miR-3960 and hsa-miR-939-5p are included in Table 3.

3.4 Transfer of exosomal miRNAs from lymphoma cell to normal B-cells

Electron microscopy analyzes of exosomes isolated from normal B-cell, and the lymphoma cell lines were sized between 60–140 nm and were found to contain specific exosomal markers. We compared the miRNA profiles of normal B cell-derived exosomes with the exosomes isolated from the cell lines before and after co-culture experiment (Fig. 4). When compared to normal B-cells, increased expression of four miRNAs (hsa-miR-1587, hsa-miR-3656, hsa-miR-4701, and hsa-miR-8071) and two miRNAs (hsa-miR-4701-3p and hsa-miR-8071) were observed in normal B-cells co-cultured with GC lymphoma cells and non-GC lymphoma cells, respectively ( $p<$ 0.001 for all six miRNAs). This finding supports that miRNAs could be transferred between the cells via exosomes. Interestingly, increased expression of hsa-miR-6127 was specifically observed in normal B-cells co-cultured with Pfeiffer and U2932 cells, while there was specifically increased expression of hsa-miR-595 in normal B cells co-cultured with Pfeiffer and U2940 ( $p<$ 0.001 for both miRNAs).

Consistent with the results from the miRNA microarray, hsa-miR-3960, hsa-miR-6089, hsa-miR-939-5p, hsa-miR-1207-5p, hsa-miR-595 were down-regulated and miR-6803-5p was up-regulated in relevant the exosome and cell samples in the validation analyses.

4. Conclusions

Consistent with previous studies [9, 17], the concentration of exosomes and total exosomal proteins were increased in the patients with DLBCL. We also found that the concentration of exosome and total protein did not correlate. These results suggested that exosomes contain specific proteins and can participate in the pathogenesis of the disease by their cargo proteins. Interestingly, the patients with Non-GC subtype had an elevated exosomal protein concentrations and we need to clarify the essential mechanisms of its contribution to the lymphomagenesis of Non-GC subtype.

The presence of $\beta$ -actin negative exosomes also reflects the success of the isolation protocol as an indicator of the absence of cellular debris contamination [18]. In addition, exosomes released from tumor cells such as colon cancer and triple-negative breast cancer have also been reported to be heterogeneous for the presence of $\beta$ -actin [18, 19]. All these results prove us that exosomes carry different macromolecules depending on cell type and body fluid type and show heterogeneity due to this difference.

Tumor-derived exosomes partially carry molecular traces of parent cells and the molecular traces distinguish tumor-derived exosomes from non-malignant exosomes as well as exosomes from different types of tumor cells [10]. Considering the protein-complexed nature of circulating miRNAs, exosomal miRNA profile has great advantages in cancer diagnosis and prognosis as well as predicting response to treatment [9, 20, 21, 22]. In the present study, we showed that the exosomes isolated from the clinical samples of DLBCL patients and DLBCL cell lines contained different miRNA profiles. Three miRNAs; miR-3960, miR-6089 and miR-939-5p, were significantly down-regulated in the plasma exosomes of DLBCL patients. Khare et al. reported that miR-124 and miR532-5p were identified as most prominently up-regulated and miR-425 and miR-145 as most prominently downregulated by next-generation sequencing in the plasma exosomes of DLBCL [23]. There are studies showing an increase of exosomal miR-155-5p and let-7g-5p in DLBCL [24, 25], but these data are not specific to DLBCL [26]. The reasons for these incompatible data can be attributed to the source, sample size, different detection methods, and lacking endogenous controls used to normalize exosomal miRNAs [27, 28]. Indeed, further functional studies are needed to determine the lymphoma-specific and the lymphoma-related miRNAs.

In our study, miR-3960 was found to be down-regulated in both plasma exosomes of DLBCL patients and all DLBCL cell lines except for the Pfeiffer cells. In a study with colon cancer cell lines and breast cancer cell lines, it was reported that the expression of miR-3960 was down-regulated [29]. In serum exosome samples of patients with colorectal cancer, miR3960 expression is down-regulated when compared to healthy individuals [30]. Interestingly, miR-3960 and miR-6089 were identified as overexpressed in plasma samples of healthy individuals [31, 32]. miR-3960 has 1100 binding sites on 375 target mRNAs, and approximately half of these binding sites are localized in protein-coding regions of mRNAs [33]. Our information about miR-6089, localized in Xp22.3, is limited. It has been reported that miR-6089 was significantly down-regulated in Multiple Myeloma patients compared to monoclonal gammopathy of undetermined significance patients [34].

It has also been reported that the tumor cell proliferation and in vitro tumor-forming abilities of cancer cells were stimulated in the absence of hsa-miR-939. In addition to, miR-939 exerts its tumor-suppressing role by targeting SLC34A2 via the inhibition of Raf-MEK-ERK signaling pathways [35]. The clinical significances and biological roles of miR-3960, miR-6089, and miR-939 in DLBCL are still not known and functional studies to find out the mechanisms of the action of the miRNAs in lymphomagenesis are needed.

The interaction between cells that make up the tumor microenvironment is extremely important in tumor development and progression. It has been shown that exosomes released from DLBCL cells were rapidly and effectively internalized by healthy B-cells, but rarely internalized by NK cells, monocytes, and T-lymphocytes [12]. Similar results were obtained from the Mantle-Cell Lymphoma study [11]. In the present study, we showed that DLBCL-derived exosomes were internalized by normal B-cells and changed the miRNA profile in the B-cells. Regardless of the cell of origin, the expression of joint miRNAs was increased in normal B-cells co-cultured with each lymphoma cell line. However, the upregulated miRNAs in normal B-cells co-cultured with lymphoma cells carrying the t(14;18) translocation and mutant p53 (Pfeiffer, SU-DHL-4) as well as lymphoma cells lacking the translocation (SU-DHL-2 and U2932) and wild-type p53 (SU-DHL-2 and U2940) were different. Although we do not have detailed information about the cargo choices/preferences of cells for packaging into exosomes, the p53-dependent regulation of TSAP6 (tumor suppressor activated pathway-6) has been shown to regulate exosome release and content [36, 37]. Another interesting study reported that 165 miRNAs were detected only in exosomes released from KRAS/p53 mutant lung cancer cells but were not detected in the cells [38]. Two deregulated miRNAs, hsa-miR-595 and hsa-miR-6127, were particularly interesting. It has been reported that miR595 overexpression reduces apoptosis in leukemia cells treated with methotrexate while hsa-miR-6127 reduces the expression of genes related to genetic packaging and organization [39, 40]. Detailed functional studies are needed to prove the relationship between the miRNAs and lymphoma aggressiveness and therapy response. In addition to, B-cell-derived exosomes are rich in non-template-directed 3’-uridylated miRNAs, whereas B-cells were mostly rich in 3’-adenylated miRNAs [41]. Therefore, we thought that the genetic background of the lymphoma cell and the identification of the codes of miRNA motifs would help us to understand the functional significance of tumor-derived exosomes in the pathogenesis of DLBCL.

In summary, the current study showed that 33 exosomal miRNAs were differentially expressed between healthy individuals and DLBCL patients and we suppose that miR-3960, miR-6089 and miR-939-5p can be used as the miRNA signature in DLBCL diagnosis. This data needs to be validated in a clinical trial with larger cohort before concluding that these markers can be used for diagnosis. In the cell-to-cell communication of lymphoma-derived exosomes, it is important to identify the genomic characterization of the lymphoma cell, as well as the identification of the molecular motifs of exosomal cargoes.

Footnotes

Acknowledgments

This study was supported by a grant from The Scientific and Technological Research Council of Turkey, TUBITAK (Grant No. 114S442). The authors are grateful to Dr. Sevil Zencir for helpful discussions and Dr.Nazan Keskin for STEM and TEM assistance.

Conflict of interest

The authors involved in this study declare no conflict of interest.

Author contributions

Conception: V.C., and G.O.C.

Interpretation or analysis of data: V.C., G.O.C., S.H., I.C.B., E.T., N.S.T., and G.C.

Preparation of the manuscript: V.C., G.O.C., S.H., I.C.B., E.T., G.B., and K.Y.

Revision for important intellectual content: K.Y.

Supervision: V.C., and G.O.C.

References

Republic of Turkey, Ministry of Health [homepage on Internet], Cancer Statistics Yearbook, (2016) [updated 2019, Ankara]. Available from https://hsgm.saglik.gov.tr/depo/birimler/kanser-db/istatistik/Trkiye_Kanser_statistikleri_2016.pdf.

Alizadeh

A.A.

Eisen

M.B.

Davis

R.E.

et al., Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling, Nature 403 (2000), 503–511.

Hans

C.P.

Weisenburger

D.D.

Greiner

T.C.

et al., Confirmation of the molecular classification of diffuse large B-cell lymphoma by immunohistochemistry using a tissue microarray, Blood 103 (2004), 275–282.

Beheshti

Stevenson

Vanderburg

et al., Identification of circulating serum multi-microRNA signatures in human DLBCL models, Scientific Reports 9 (2019), 17161.

Larrabeiti-Etxebarria

Lopez-Santillan

Santos-Zorrozua

et al., Systematic review of the potential of microRNAs in Diffuse Large B Cell Lymphoma, Cancers 11 (2019), 144.

Lopez-Santillan

Larrabeiti-Etxebarria

Arzuaga-Mendez

et al., Circulating miRNAs as biomarkers in Diffuse Large B-cell Lymphoma: A systematic review, Oncotarget 9 (2018), 22850–22861.

Kamal

N.N.S.B.N.K.

and Shahidan

W.N.Z.

, Non-exosomal and exosomal circulatory microRNAs: which are more valid as biomarkers? Frontiers Pharmacology 10 (2019), 1500.

LeBleu

V.S.

and Kalluri

, Exosomes as a multicomponent biomarker platform in cancer, Trends Cancer S2405-8033 (2020), 30116–3.

Rutherford

S.C.

Fachel

A.A.

et al., Extracellular vesicles in DLBCL provide abundant clues to aberrant transcriptional programming and genomic alterations, Blood 132 (2018), e13–e23.

10.

Whiteside

T.L.

, Tumor-derived exosomes and their role in cancer progression, Advances in Clinical Chemistry 74 (2016), 103–141.

11.

Hazan-Halevy

Rosenblum

Weinstein

et al., Cell- specific uptake of mantle cell lymphoma-derived exosomes by malignant and non-malignant B-lymphocytes, Cancer Letters 364 (2015), 59–69.

12.

Bennit

H.R.F.

Amber

Oppegard

L.J.

et al., Uptake of lymphoma-derived exosomes by peripheral blood leukocytes, Blood and Lymphatic Cancer 7 (2017), 9–23.

13.

McDonald

M.K.

Capasso

K.E.

and Ajit

S.K.

, Purification and microRNA profiling of exosomes derived from blood and culture media, Journal of Visualized Experiments 76 (2013), e50294.

14.

Lötvall

Hill

A.F.

Hochberg

et al., Minimal experimental requirements for definition of extracellular vesicles and their functions: a position statement from the International Society for Extracellular Vesicles, Journal of Extracellular Vesicles 3 (2014), 26913.

15.

Eitan

Green

Bodogai

et al., Age-related changes in plasma extracellular vesicle characteristics and internalization by leukocytes, Scientific Report 7 (2017), 1342.

16.

Shelke

G.V.

Lässer

Gho

Y.S.

et al., Importance of exosome depletion protocols to eliminate functional and RNA-containing extracellular vesicles from fetal bovine serum, Journal of Extracellular Vesicles 3 (2014), 24783.

17.

Barıs

I.C.

Hacıoglu

Turk

N.S.

et al., Expression and DNA methylation profiles of EZH2-target genes in plasma exosomes and matched primary tumor tissues of the patients with diffuse large B-cell lymphoma, Clinical and Translational Oncology (2020), 1152–1166.

18.

Fernandez-Palomo

McNeill

F.E.

et al., Exosomes are released by bystander cells exposed to radiation-induced biophoton signals: Reconciling the mechanisms mediating the bystander effect, PLoS One 12 (2017), e0173685.

19.

McCready

Sims

J.D.

Chan

et al., Secretion of extracellular hsp90alpha via exosomes increases cancer cell motility: a role for plasminogen activation, BMC Cancer 10 (2010), 294.

20.

Vickers

K.C.

Palmisano

B.T.

Shoucri

B.M.

et al., MicroRNAs are transported in plasma and delivered to recipient cells by high-density lipoproteins, Nature Cell Biology 13 (2011), 423–433.

21.

Fang

Zhu

D.X.

Dong

H.J.

et al., Serum microRNAs are promising novel biomarkers for diffuse large B cell lymphoma, Ann Hematology 91 (2012), 553–559.

22.

Iqbal

Shen

Huang

et al., Global microRNA expression profiling uncovers molecular markers for classification and prognosis in aggressive B-cell lymphoma, Blood 125 (2015), 1137–1145.

23.

Khare

Goldschmidt

Bardugo

et al., Plasma microRNA profiling: Exploring better biomarkers for lymphoma surveillance, PLoS One 12 (2017), e0187722.

24.

Bradshaw

Sutherland

H.G.

Haupt

L.M.

et al., Dysregulated microrna expression profiles and potential cellular, circulating and polymorphic biomarkers in non-hodgkin lymphoma, Genes (Basel) 7 (2016), 130.

25.

Zare

Javanmard

S.H.

Mehrzad

et al., Evaluation of exosomal mir-155, let-7g and let-7i levels as a potential noninvasive biomarker among refractory/relapsed patients, responsive patients and patients receiving R-CHOP, Leukemia Lymphoma 60 (2019), 1877–1889.

26.

Paggetti

Haderk

Seiffert

et al., Exosomes released by chronic lymphocytic leukemia cells induce the transition of stromal cells into cancer-associated fibroblasts, Blood 126 (2015), 1106–1117.

27.

Jørgensen

Baek

Pedersen

et al., Extracellular Vesicle (EV) array: microarray capturing of exosomes and other extracellular vesicles for multiplexed phenotyping, Journal Extracellular Vesicles (2013), 2.

28.

Matsuzaki

and Ochiya

, Circulating microRNAs and extracellular vesicles as potential cancer biomarkers: a systematic review, International Journal of Clinical Oncology 22 (2017), 413–420.

29.

Reza

A.M.M.T.

Choi

Y.J.

Yuan

Y.G.

et al., MicroRNA-7641 is a regulator of ribosomal proteins and a promising targeting factor to improve the efficacy of cancer therapy, Scientific Report 7 (2017), 8365.

30.

Yan

Han

Gao

et al., Exosome-encapsulated microRNAs as circulating biomarkers for colorectal cancer, Oncotarget 8 (2017), 60149–60158.

31.

Hruštincová

Votavová

and Dostálová

M.M.

, Circulating microRNAs: methodological aspects in detection of these biomarkers, Folia Biologica (Praha) 61 (2015), 203–218.

32.

Ferrero

Cordero

Tarallo

et al., Small non-coding RNA profiling in human biofluids and surrogate tissues from healthy individuals: description of the diverse and most represented species, Oncotarget 9(2017), 3097–3111.

33.

Ivashchenko

Berillo

Pyrkova

et al., MiR-3960 binding sites with mRNA of human genes, Bioinformation 10 (2014), 423–427.

34.

Desantes

Ilaria

Luca

et al., MicroRNA profile in bone marrow fibroblasts from patients with multiple myeloma, EHA Library 100347 (2015), E1244.

35.

Zhang

J.X.

Gao

et al., Decreased expression of miR-939 contributes to chemoresistance and metastasis of gastric cancer via dysregulation of SLC34A2 and Raf/MEK/ERK pathway, Molecular Cancer 16 (2017), 18.

36.

Lespagnol

Duflaut

Beekman

et al., Exosome secretion, including the DNA damage-induced p53-dependent secretory pathway, is severely compromised in TSAP6/Steap3-null mice, Cell Death and Differentiation 15 (2008), 1723–1733.

37.

Cooks

Pateras

I.S.

Jenkins

et al., Mutant p53 cancers reprogram macrophages to tumor supporting macrophages via exosomal miR-1246, Nature Communication 9 (2018), 771.

38.

Trivedi

Talekar

Shah

et al., Modification of tumor cell exosome content by transfection with wt-p53 and microRNA-125b expressing plasmid DNA and its effect on macrophage polarization, Oncogenesis 5 (2016), e250.

39.

Wang

S.M.

Sun

L.L.

W.S.

et al., MiR-595 suppresses the cellular uptake and cytotoxic effects of methotrexate by targeting SLC19A1 in CEM/C1 cells, Basic & Clinical Pharmacology & Toxicology 123 (2018), 8–13.

40.

Tubita

Segui-Barber

Lozano

J.J.

et al., Effect of immunosuppression in miRNAs from extracellular vesicles of colorectal cancer and their influence on the pre-metastatic niche, Scientific Reports 9 (2019), 11177.

41.

Koppers-Lalic

Hackenberg

Bijnsdorp

I.V.

et al., Nontemplated nucleotide additions distinguish the small RNA composition in cells from exosomes, Cell Reports 8 (2014), 1649–1658.