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\begin{document}

\title{Exosomes as Liquid Biopsy Biomarkers in Diffuse Large B-cell Lymphoma
(DLBCL)- Current State-of-the-Art and Unmet Clinical Needs}



\author[1]{Kenneth Ofori}%
\author[2]{Govind Bhagat}%
\author[2]{Alex Rai}%
\affil[1]{Columbia University Irving Medical Center}%
\affil[2]{Affiliation not available}%


\vspace{-1em}



  
  \date{June 16, 2024}


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\selectlanguage{english}
\begin{abstract}
Diffuse Large B-Cell Lymphoma is the most common type of Non-Hodgkin's
Lymphoma. The disease exhibits significant clinical and biologic
heterogeneity. Treatment with standard first line therapy results in
cure in about 60\% of patients while 30-40\%of patients either are
refractory to therapy or relapse. Current prognostic scores and
biomarkers are unable to accurately predict patients who would relapse
or would have refractory disease. A part of the heterogeneity in the
behavior of DLBCL is explained by the cell of origin of the tumor.
Germinal center type (GCB) DLBCL which is derived from centroblasts are
associated with better prognosis compared with activated B-cell type
(ABC), which is derived from a B-cell committed to secretory
differentiation. While the gold standard for cell of origin
determination is gene expression profiling, immunohistochemical methods
are routinely used because of more readily available fixed tissue and
expertise. Immunohistochemical methods are however associated with a
significant degree of discordance with GEP. Within the ABC and GCB types
of DLBCL, subgroups of prognostic significance have been identified
using various multiple approaches which do not inure themselves to
routine practice partly because of limitation of diagnostic material or
expertise. Exosomes are a class of membrane bound extracellular vesicles
of endosomal origin, produced by multiple cell types. They are involved
in intercellular communication and present in abundance in various
bodily fluids. Exosomal cargo which includes nucleic acids and proteins
can be analyzed, yielding diagnostic and prognostic information in
management of DLBCL.%
\end{abstract}%



\sloppy




\textbf{Introduction}

Diffuse large B-Cell lymphoma (DLBCL) is the most common type of Non
Hodgkin Lymphoma (NHL) constituting 30-40\% of cases (1,2,3). An
estimated 27,650 new cases were diagnosed in 2016 with 25,380 of them
being the not otherwise specified (NOS) variant (4). DLBCL shows a
slight male predominance (55\%) and the median age at diagnosis is 64
years, but the disease affects all age groups and age of onset is
earlier in African Americans (5,6). The 5-year survival rate shows mild
geographic variation, 62\% in the US (7) and 55.4\% in Europe (8).

DLBCL, despite its relative morphologic homogeneity, represents
heterogeneous entities, with disparate biological and clinical
manifestations. Outcome of disease to standard first line therapy,
R-CHOP, consisting of rituximab, cyclophosphamide, doxorubicin,
vincristine, and prednisone plus the monoclonal antibody rituximab, is
variable. Twenty to fifty percent of patients are either refractory to
therapy without remission or relapse after complete remission (9,10,11)

Relapsed disease is associated with a poor prognosis and patients with
early disease relapse have a worse prognosis compared to those with late
relapses (12). The mechanisms for relapse are purportedly different for
these two groups (13). The prognosis for refractory patients, patients
whose disease fails to go into remission or progress with induction
therapy, is even more dismal compared to early and late relapse disease
(14). While patients with relapse and refractory disease might have had
need for more aggressive first line therapies, there are currently no
biomarkers that adequately predict at diagnosis, the patients who are
likely to be refractory to therapy, relapse after initial remission, or
the time of relapse whether early or late. Similarly, once treatment
commences or remission is achieved, there are no biomarkers that can
accurately predict subsequent behavior of the disease. In addition, in
refractory and relapsed disease, biomarkers capable of predicting
response to second or additional lines of therapy remain elusive. Thus,
there exists an urgent, unmet clinical need for biomarkers that address
these challenges in management of DLBCL.

Current disease stratification systems/methods and assays

\emph{International Prognostic Index for Risk Stratification of DLBCL
patients}

The International Prognostic Index (IPI) and its revised variant, R-IPI
are widely used clinical prognostication systems for DLBCL (15,16).
These indices use a combination of age, Eastern Cooperative Oncology
Group (ECOG) performance status, tumor stage, lactate dehydrogenase
level, and the number of extra nodal sites of disease to predict the
prognosis of patients with DLBCL (17). Biccler et al showed the poor
performance of the IPI in predicting overall survival in DLBCL patients.
(18) In a study investigating the ability of the IPI and the revised
index to predict outcome, R-IPI identified three distinct prognostic
groups with: (a) very good (4-year progression-free survival {[}PFS{]}
94\%, overall survival {[}OS{]} 94\%), (b) good (4-year PFS 80\%, OS
79\%), and (c) poor (4-year PFS 53\%, OS 55\%) outcomes, respectively
(P\textless{} 0.001) (19). However, neither the R-IPI nor IPI are unable
to predict patients with \textless{}50\% chance of survival. Such
patients potentially need more potent first lines of therapy. However,
there are no biomarkers that can reliably identify these high risk
patients as of yet.

\emph{Cell of Origin (COO) determination}

The cell of origin of DLBCL explains part of the heterogeneity of the
disease. Using gene expression profiling, DLBCL NOS was initially
classified into germinal center B cell (GCB), activated B-cell (ABC),
and non-classifiable types (20). GCB type DLBCL is thought to derive
from centroblasts while the ABC type has features reminiscent of a
B-cell committed to terminal B-cell differentiation (21) (see Figure 1).

The COO classification could predict overall survival of DLBCL patients
and response to R-CHOP therapy. The GCB subtype has a more favorable
prognosis compared to the ABC subtype. (22,23,24,25). Determination of
cell of origin also has implications on drug therapy in
relapsed/refractory disease. Recently, ibrutinib, a BCR inhibitor was
found to be effective in relapsed and refractory ABC type DLBCL (26).

The gold standard method for determining COO has been gene expression
profiling (GEP) (27). This modality, however, is not available at all
centers and many assays require fresh tissue, which may not always be
available. In routine practice, various immunohistochemistry (IHC) based
algorithms (see Figure 2) such as Hans, Tally, Choi and Visco-Young are
used to determine COO for DLBCL (28,29,30,31). IHC methods for COO
assignment are more practical and widely available, but are plagued by
inter-observer variability that can result in discordant classification
compared with the gold standard. Guti\selectlanguage{ngerman}érrez-García et al demonstrated
that when compared with GEP, different IHC algorithms; Colomo, Hans,
Muris, Choi, and Tally, misclassified cases at a higher rate when
defining the GCB subset: 41\%, 48\%, 30\%, 60\%, and 40\%, respectively
(32). Gene-expression profiling and not immunophenotypic algorithms
predicts prognosis in patients with diffuse large B-cell lymphoma
treated with immunochemotherapy. In this study, while the~GEP-defined
groups showed significantly different 5-year progression-free survival
(76\% vs 31\% for GCB- and ABC- DLBCL) and overall survival (80\% vs
45\%), none of the IHC algorithms retained the prognostic impact of the
COO groups (GCB vs non-GCB). Other studies have also suggested that IHC
algorithms may not have the same prognostic impact as other methods of
COO determination (33,34,35). These results underscore the unmet
clinical need for a methodology that uses readily available biopsy
material for accurate COO classification, concordant with GEP while
maintaining prognostic utility.

The COO classification is not without limitations however. COO does not
explain all the heterogeneity in the behavior and prognosis of DLBCL.
Using various approaches, subgroups within ABC showing favorable
prognosis have been identified and adverse prognostic groups have also
been identified for the GCB type. In a study involving 574 DLBCL biopsy
samples using exome and transcriptome sequencing, array-based DNA
copy-number analysis, and targeted amplicon resequencing of 372 genes to
identify genes with recurrent aberrations, Schmitz et al. identified
four DLBCL genetic subtypes: BN2, EZB, N1, and MCD, with the former two
determined to have favorable prognosis and the latter two associated
with poor prognosis (36). Progression free survival and overall survival
varied significantly within these groups. Of note, heterogeneity in
behavior within the ABC group could be identified, with inferior
survival in the MCD and N1 subtypes of ABC and favorable survival in the
BN2 subtype. In GCBs, EZB subtype had a worse predicted 5-year survival
compared with other GCBs non-classifiable by this system. Significant
independent and additive contributions to survival by gene expression
profiling (ABC vs GCB) were noted in this genetic subtyping model.

Chapuy et al used a combination of recurrent mutations, somatic copy
number alterations

and structural variants (SV) to identify five distinct groups of DLBCL
including a hitherto unappreciated group of ABC-DLBCL with favorable
prognosis (37). They also identified a subtype of GCB-DLBCL with poor
prognosis characterized by mutations and structural variants
of\emph{BCL2,} mutations in \emph{PTEN} and chromatin modifiers such
as\emph{KMT2D} ,~\emph{CREBBP} , and~\emph{EZH2} and
focal\emph{10q23.31/PTEN} ~loss. These subgroups within the different
COO types provide insight not only for prognosis but also suggest
possible mechanisms for therapeutic intervention. In spite of the
usefulness of these multiparametric approaches for classification, it
will be challenging to apply these genetic classification models in the
clinical settings due to limitations in the amount of diagnostic
material available, resources and bioinformatics expertise.

Disease Monitoring During Therapy

The rationale of using multiple agent chemotherapies in the treatment of
cancers is to avoid development of resistance, but resistance does
develop regardless of the type and combination of therapy. The
neoplastic cells may develop adaptive resistance to chemotherapy in the
course of treatment. Serial tumor profiling can provide insight into the
pathways mediating adaptive resistance and identify targets for novel
therapeutic drug development to overcome the resistance mechanisms (38).
Real time analysis may also allow prompt detection of resistance and
suggest alteration of therapy if signatures of resistance portending
refractoriness or relapse are detected. In DLBCL patients, it is not
usually feasible to obtain tissue regularly for such profiling without
invasive measures, which cause patient discomfort and increase the risk
of infections from multiple biopsy procedures. Thus, a non-invasive
method for tissue sampling at multiple time points would be of great
benefit.

Post Treatment Surveillance

The role of post-therapy or remission imaging surveillance in the
management of DLBCL patients is controversial. While the National
Comprehensive Cancer Network (NCCN) and European Society of Medical
Oncology (ESMO) guidelines recommend surveillance imaging for stage
III/IV disease for the first two years after completion of front-line
therapy (39), the 2014 Lugano classification system advises against
routine surveillance imaging (40). The positive predictive value of post
treatment PET is low, resulting in patient anxiety and increased costs
for these unnecessary medical procedures (41,42). Studies have also
failed to establish a survival advantage in imaging detected disease
relapse (43,44). Realization of the lack of survival benefit of
surveillance imaging has resulted in decreased rates of surveillance,
although this practice is still quite frequent, with over half of DLBCL
patients diagnosed in 2014-2016 undergoing surveillance imaging (45).
Thus, there is a pressing need for more specific and sensitive methods
for detecting recurrence of disease while also avoiding risks of
radiation exposure (46).

Novel Methodologies in DLBCL Management- Liquid Biopsy Based Approaches

Liquid biopsy techniques which involve assessment of cancer related
biomarkers in bodily fluid samples, have potential to resolve the unmet
clinical needs in management of DLBCL. Common liquid biopsy techniques
include circulating tumor cells (CTC), circulating tumor DNA (ctDNA) and
exosomes.

\emph{Circulating Tumor Cells}

Circulating tumor cells are neoplastic cells that are passively shed or
actively intravasate into circulation from primary tumors and/or
metastatic deposits. (47). The number of CTCs in cancer patients
correlate with treatment outcome and overall survival (48). The DNA, RNA
and protein content of CTCs can be evaluated for molecular
characterization informative of native tumor tissue (49). CTCs
constitute a small fraction of cells in circulation-1 in
10\textsuperscript{9} cells (50) and thus various techniques using
distinct biological and physical properties of CTCs are used to
differentiate and isolate them from leucocytes, erythrocytes and other
cells in a blood sample. The predominant method of CTC isolation
involves enrichment for cells with EPCAM expression and lack of CD45
expression (51,52,53). This is not applicable to circulating DLBCL cells
and cells from other hematological malignancies which express CD45 and
lack EpCAM expression. In addition, the low abundance of CTCs makes
their use in early stage of disease challenging. Other challenges with
use of CTC as liquid biopsy is the need for prompt processing of whole
blood after collection in most isolation platforms (54) precluding the
potential for biobanking specimens for future analyses or use of
archival biobanked specimens for studies.

\emph{Cell free DNA and Cell tumor DNA}

Non cell bound DNA fragments are shed into circulation as cell free DNA
(cfDNA). Circulating tumor DNA (ctDNA) which is cfDNA from tumor cells
is shed into blood through apoptosis, necrosis or through an active
process from neoplastic cells. Molecular aberrations in tumor tissues
such as point mutations, insertions, deletions and methylation profiles
are present in these circulating DNA fragments (55,56,57,58,59). The
fragmentation pattern of ctDNA in healthy people has been found to be
different from the pattern in patients with various kinds of cancers
(60). Surveillance circulating tumor DNA identifies patients at risk of
recurrence in DLBCL with a positive predictive value of 88.2\% and
negative predictive value of 97·8\% (61). Unlike CTCs and exosomes which
contain RNA and proteins together with DNA, ctDNA provides no proteomic
and transcriptomic information.

Immunoglobulin gene rearrangement is another novel technology for
identifying prognostic groups in DLBC. Molecular characterization of
immunoglobulin gene rearrangements revealed distinct subgroups in
non-GCB (62). DLBCL patients with immunoglobulin gene rearrangement have
been shown to have a lower rate of complete remission and significantly
poorer survival. (63).

\emph{Exosomes}

Exosomes are membrane-bound vesicles ranging from 30-120 nm in diameter,
and are released upon fusion of multi-vesicular bodies with the cell
membrane (64,65,66). The contents of exosomes include proteins, nucleic
acids, lipids and sugars, and they are thought to be involved in
intercellular communication (67,68,69,70,71). Exosomes are endosome
derived extracellular vesicles. Early endosomes are formed from internal
budding of the cell membrane with accompanying membrane proteins and
lipids into the cytoplasm. As the endosome matures, there is transport
of cytosolic, golgi and nuclear cargo such as nucleic acids, proteins
and other metabolites into the lumen of the endosome. There is
subsequently intravesicular budding of the endosomal membrane, forming
multivesicular bodies (MVB). The MVB fuses with the cell membrane
releasing its vesicles as exosomes into the extracellular space.
Involvement of the endosomal pathway differentiates exosomes from
microvesicles and apoptotic bodies which are the other extracellular
vesicles. Microvesicles and apoptotic bodies are larger vesicles formed
from outward budding of the cell membranes from living and dying cells
respectively, into the extracellular space (72)

Mechanisms by which recipient cells take up exosomes include
macropinocytosis, receptor or lipid raft mediated endocytosis,
phagocytosis, or direct fusion with the recipient cell membrane (73).
Exosomes are found in many body fluids including blood, urine,
cerebrospinal fluid, amniotic fluid, saliva, breast milk, peritoneal
fluid, etc. (74).

\emph{Exosome Isolation Methods}

There are various methods for isolating exosomes with varying degrees of
complexity and contamination with non-exosomal vesicles and/or
non-vesicular products. The prevalent method for exosome isolation is
differential ultracentrifugation. It involves sequential spinning of a
fluid at increasing speed and duration to pellet dead cells and cellular
debris, microvesicles and eventually, exosomes (75). This method is not
suitable for fluids with high viscosity such as blood since higher
speeds and longer duration of centrifugation are required (76). Due to
similarity of sedimentation properties of various types of extracellular
vesicles the yield and purity using this method may be low (77,78)

Density gradient ultracentrifugation uses a concept similar to
differential ultracentrifugation. The initial steps are similar to DUC
but sucrose is added at a later point. Due to the buoyant density of
exosomes (1.15 to 1.19 g/mL) in sucrose, it sediments separately from
other denser extracellular vesicles during centrifugation (79,80). This
method yields purer fractions compared with differential
ultracentrifugation (81), but has same disadvantage of need for long
periods of processing and requirement of costly equipment.

Size based isolation techniques make use of the smaller size of exosomes
compared with microvesicles, apoptotic bodies and other molecules to
separate them in a fluid sample. Ultrafiltration, a size based technique
uses membrane filters with decreasing pore sizes to isolate exosomes
(82). It is a faster method compared with ultracentrifugation and does
not require costly equipment. While this method yields pure vesicles,
there is difficulty in removing contaminating proteins but can be
combined with ultrcentrifugation for removal of proteins (83). Other
size based techniques include size exclusion chromatography which
involves differential passage of various vesicles and particles through
a gel column and their recovery in different elution fractions (84). SEC
allows for pure exosomal isolates with intact physical characteristics
(85). The run time is however long and limits its use in multiple
biological specimens.

In polymer-based precipitation, a polymer, e.g. polyethylene glycol
(PEG) precipitates exosomes in a biofluid and the exosomes recovered by
low speed centrifugation to pellet down the precipitate (86).

Immunoaffinity enrichment methods use exosomal membrane markers,
typically the tetraspanins CD9, CD63 and CD81, to isolate exosomes from
biofluids (87,88). The antibodies are immobilized on varying media
including magnetic beads, microfluidic devices and chromatography
matrices (89,90).

Newer methods of exosome isolation include contact-free sorting which
uses ultrasound waves to exert differential acoustic forces on vesicles
based on their size and density (91), microfluidics, which utilizes size
dependent position of flow of various vesicles in a biofluid in a
channel to isolate exosomes (92) and nanoplasmon-enhanced scatter which
uses immobilized exosomal antibodies and gold plated nanoparticles to
capture and detect exosomes based on scatter patterns (93). Confirmation
of exosome isolation can be done using multiple techniques including
electron microscopy which identifies the typical cup shaped morphology
and vesicle size of 30-120nm, western blotting for exosome markers such
as tetraspanins (CD63/CD9/CD81), ALIX, flotillin, hsp70, TSG101, and
also nanoparticle tracking analysis for vesicle size and concentration
determination (94).

Exosome Use in DLBCL

Due to their relative abundance, longer half-life, presence in multiple
body fluids, and a payload that includes nucleic acids, proteins, and
small molecules (95) exosomes are poised to contain biomarkers that may
be informative in the prognostication and management of DLBCL patients
at multiple stages. The nucleic acid and/or protein cargo in exosomes
can be used for molecular analyses in DLBCL. Considering the relative
abundance of exosomes in body fluids, especially serum where there is a
concentration of about 3x10\textsuperscript{6} exosomes/microliter, this
presents a readily available source of biologic material for
multiparametric studies leading to more exhaustive characterization of
DLBCL types, prognostication, surveillance during and post treatment,
and understanding of mechanisms of resistance to therapy. Rutherford et
al characterized mutations in cell lines and their exosomes using RNA
sequencing and found that nearly one third of mutations in the cell
lines were detected in the exosomes (96). This was surprising as
exosomes contained a smaller subset of RNAs than the cell lines, a
finding that also suggests a likely enrichment of mutated RNA in
exosomes.

\emph{Exosomes as Prognostic Markers in DLBCL}

Evaluation of exosomal nucleic acids can also provide additional
prognostic information. Feng et al. found that circulating exosomal
expression of miR-99a-5p and miR-125b-5p were significantly higher in
chemoresistant vs. chemosensitive DLBCL patients (p\textless{}0.001)
(97). Determination of predictive value of these miRNA using ROC curve
analysis showed that the area under the curve (AUC) values of
miR-99a-5p, miR-125b-5p, and IPI scores were 0.744 (p \textless{}
0.001), 0.7802 (p \textless{} 0.001), and 0.6308 (p \textless{} 0.05),
respectively. The combined predictive value of miR-99a-5p and IPI score,
had AUC of 0.8326 (p \textless{} 0.001) while that of miR-125b-5p
combined with IPI score, had an AUC of 0.8143 (p \textless{} 0.001).
This suggests that determination of exosomal expression of miR-99a or
miR-125b-5p, when combined with IPI may be a robust way to predict
response to therapy. Zare et al. observed a significant increase in
exosomal miR-155 levels in refractory/relapsed DLBCL patients compared
to responding patients or patients still on R-CHOP therapy (98). They
also observed a higher concentration in refractory/relapsed patients.

\emph{Exosomes in Post Therapy Surveillance}

Exosomes and their associated cargo hold promise in their application as
a non-invasive biomarker for DLBCL patients. They could be of great
benefit in post treatment surveillance of DLBCL patients as a means to
avoid radiation exposure of PET scans and unnecessary testing associated
with false-positive PET scans. Di et al identified a panel of five
circulating exosomal miRNAs as noninvasive biomarkers of DLBCL
consisting of hsa-miR-379-5p, hsa-miR-135a-3p, hsa-miR-4476,
hsa-miR-483-3p and hsa-miR-451a (99). hsa-miR-379-5p, hsa-miR-135a-3p,
hsa-miR-4476 were overexpressed in DLBCL compared to healthy controls,
while hsa-miR-483-3p and hsa-miR-451a were expressed at lower levels.
The panel had an AUC of 0.951 (95\% CI0.847-0.993) in the testing phase,
0.841 (95\% CI, 0.767-0.900) in the validation phase and 0.824 (95\% CI,
0.760-0.877) in the combined testing and validation phase.

\emph{Exosomes as Mediators of Resistance and Targets for New Therapies}

Exosomes play crucial roles in survival of lymphoma cells, evasion of
immune response and resistance to therapy. Poggio et al showed that
exosomal PD-L1 suppressed T-cell function in lymph nodes draining tumor
sites, and promoted tumor growth across different tumor types (100.).
Local blockade of exosomal PD-L1, inhibited growth of tumor locally as
well as at distant sites injected synchronously or at a later time to
the PD-L1 block.

Tumor derived exosomes contain tumor antigens and MHC-I and MHC-II
molecules allowing direct presentation and activation of CD8 and CD4
T-cells and cross presentation to T cells via transfer to antigen
presenting cells (101,102) . Whether these mechanisms are also
operational in DLBCL remains to be determined. Studies of exosomes have
provided insights to mechanisms of resistance in DLBCL and possible
targets for new therapy. Chen et al showed a dual role of tumor derived
exosomes (TEX) in DLBCL (103.). DLBCL exosomes when incubated with
dendritic cells (DC) resulted in increased proliferation and activation
of dendritic cells. The dendritic cells were able to cause greater T
cell expansion after incubation with the exosomes. Tumor derived
exosomes however resulted in increased PD-1 expression and increased
apoptosis of Th2 cells. They also demonstrated that the TEXs play a role
in enhancing cell proliferation, invasion, migration, and angiogenesis
with promotion of tumor growth in vivo. Their findings suggest a role
for targeting exosome inhibition in developing new therapies for DLBCL
or use of exosome derived vaccines to augment the anti-lymphoma immune
response.

Koch et al demonstrated the presence of side population (SP) cells in
DLBCL, which have stemness properties and are capable of propagating
tumor growth (104). They showed an equilibrium of SP and non-SP cells,
with no stemness properties, whereby exosome mediated Wnt signaling
transformed non-SP cells to SP cells, and vice versa.

Exosomes have been shown to play a role in drug resistance of
hematopoietic malignancies to therapy. Koch et al showed that after
initial accumulation in the nucleus, the site of action of doxorubicin
and pixantrone, these chemotherapeutic agents are exported into exosomes
and then released from the cell, leading to reduced amount of drug at
the site of action and development of resistance (105). They showed that
inhibition of ABCA3, a protein involved in the transport of these drugs
into exosomes resulted in trapping of the drugs in the nucleus and
higher sensitivity to doxorubin and pixantrone.

Exosomal CD20 has also been shown to shield DLBCL cells from anti-CD20
immunotherapy providing a mechanism for evading this therapy (106). This
mechanism of resistance was again attenuated by inhibition of ABCA3
which is involved in exosome biogenesis. Serial profiling of exosomal
nucleic acids and/or proteins during therapy may identify more products
involved in resistance and help develop a resistance signature during
therapy that necessitates prompt therapy changes. It could also help
guide development of new therapeutic targets.

\textbf{Challenges and Concluding Thoughts}

Since exosomes are released by multiple cell types, an obvious challenge
in the use of exosomal cargo or liquid biopsy techniques in general as
biomarkers of DLBCL is the enrichment of tumor specific exosomes in
order to avoid dilution of information in tumor exosomes by exosomes
from non-neoplastic tissue. Enrichment for tumor derived exosomes before
subsequent analysis of exosomal cargo would address the issue of
background noise from non-neoplastic exosomes. Castillo et al identified
specific surface proteins on prostate cancer cell lines derived exosomes
and used antibodies to these proteins for immunocapture in plasma of
prostate cancer patients to enrich for tumor derived exosomes for
downstream analysis of the tumor derived exosomal cargo (107). Mizutani
et al also demonstrated isolation of prostate cancer specific exosomes
using immunocapture with prostate specific antibodies. (108) Similar
approaches can be employed as pre-analytical step in studying exosomes
in fluids from DLBCL patients.

Another challenge in routine use of exosomes in cancer management is the
difference in detected cargo observed using different methods of
isolation. Jeppesen et al used high resolution gradient fractionation to
separate small extracellular vesicles from non-vesicular proteins and
direct immunoaffinity capture to isolate exosomes from other vesicles
(109). Analyses of these exosomes showed absence in the cargo of some
nucleic acids and proteins hitherto found to be present in exosomes
using other methods. Contamination of exosomal isolates by other
vesicles and non-vesicular molecules probably accounts for such
variation. Guidelines to confirm purity of isolation would need to be
developed to prevent inter-laboratory variation of exosomal content
analyses.

Exosomes thus have great potential for not only improving diagnosis,
prognostication, and monitoring of DLBCL, but provide a means of
understanding the biology of DLBCL with the ultimate goal of improving
care for patients.

\textbf{References}

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